Integrated insulin delivery system with continuous glucose sensor

ABSTRACT

Systems and methods for integrating a continuous glucose sensor  12 , including a receiver  14 , a medicament delivery device  16 , a controller module, and optionally a single point glucose monitor  18  are provided. Integration may be manual, semi-automated and/or fully automated.

INCORPORATION BY REFERENCE TO RELATED APPLICATIONS

Any and all priority claims identified in the Application Data Sheet, orany correction thereto, are hereby incorporated by reference under 37CFR 1.57. This application is a continuation of U.S. application Ser.No. 13/885,604, filed on May 15, 2013, which is the national phase under35 U.S.C. §371 of prior PCT International Application No.PCT/US2007/080848 filed on Oct. 9, 2007. Each of the aforementionedapplications is incorporated by reference herein in its entirety, andeach is hereby expressly made a part of this specification.

FIELD OF THE INVENTION

The present invention relates generally to systems and methodsmonitoring glucose in a host. More particularly, the present inventionrelates to an integrated medicament delivery device and continuousglucose sensor.

BACKGROUND OF THE INVENTION

Diabetes mellitus is a disorder in which the pancreas cannot createsufficient insulin (Type I or insulin dependent) and/or in which insulinis not effective (Type 2 or non-insulin dependent). In the diabeticstate, the victim suffers from high glucose, which may cause an array ofphysiological derangements (for example, kidney failure, skin ulcers, orbleeding into the vitreous of the eye) associated with the deteriorationof small blood vessels. A hypoglycemic reaction (low glucose) may beinduced by an inadvertent overdose of insulin, or after a normal dose ofinsulin or glucose-lowering agent accompanied by extraordinary exerciseor insufficient food intake.

Conventionally, a diabetic person carries a self-monitoring bloodglucose (SMBG) monitor, which typically comprises uncomfortable fingerpricking methods. Due to the lack of comfort and convenience, a diabeticgenerally measures his glucose level only two to four times per day.Unfortunately, these time intervals are spread so far apart that thediabetic will likely find out too late that he has entered a hyper- orhypo-glycemic condition, sometimes incurring dangerous side effects. Infact, it is not only unlikely that a diabetic will take a timely SMBGvalue, but he will not know if his blood glucose is going up (higher) ordown (lower), which inhibits his ability to make educated insulintherapy decisions.

Home diabetes therapy requires personal discipline of the user,appropriate education from a doctor, proactive behavior undersometimes-adverse situations, patient calculations to determineappropriate therapy decisions, including types and amounts ofadministration of insulin and glucose into his or her system, and issubject to human error. Technologies are needed that ease the burdensfaced by diabetic patients, simplify the processes involved in treatingthe disease, and minimize user error which may cause unnecessarilydangerous situations in some circumstances.

SUMMARY OF THE INVENTION

In a first aspect, an integrated system for monitoring a glucoseconcentration in a host and for delivering insulin to a host isprovided, the system comprising a continuous glucose sensor, wherein thecontinuous glucose sensor is configured to substantially continuouslymeasure a glucose concentration in a host, and to provide sensor dataassociated with the glucose concentration in the host; an electronicsmodule comprising an on/off controller module configured to iterativelydetermine an insulin therapy instruction in response to an evaluation ofa relationship of internally derived data and a glucose boundary,wherein the insulin therapy instruction comprises an instructionselected from the group consisting of on and off; and an insulindelivery device configured to deliver insulin to the host, wherein theinsulin delivery device is at least one of physically connected to areceiver and operably connected to a receiver, wherein the insulindelivery device is configured to receive the insulin therapy instructionfrom the controller.

In an embodiment of the first aspect, the insulin therapy instruction isdetermined solely on internally derived data and the glucose boundary.

In an embodiment of the first aspect, the glucose boundary isprogrammable by at least one of the host, a caretaker of the host, theon/off controller module, and a manufacturer of the integrated system.

In an embodiment of the first aspect, the glucose boundary is a glucoseconcentration of from about 70 mg/dl to about 160 mg/dl.

In an embodiment of the first aspect, an on insulin therapy instructionis determined when the glucose concentration exceeds the glucoseboundary.

In an embodiment of the first aspect, the insulin delivery device isconfigured to deliver insulin automatically in response to selection ofthe on insulin therapy instruction.

In an embodiment of the first aspect, the insulin is flash insulin.

In an embodiment of the first aspect, the insulin delivery device isfurther configured to deliver insulin at a programmable delivery rate,wherein the delivery rate is programmable by at least one of the host, acaretaker of the host, the on/off controller module, and a manufacturerof the system.

In an embodiment of the first aspect, the insulin delivery device isfurther configured to deliver insulin at a programmed delivery rate andwherein the on/off controller module is configured to iterativelydetermine the insulin therapy instruction in response to internallyderived data and the glucose boundary, wherein the on/off controllermodule comprises programming configured to adjust an insulin deliveryrate in response to internally derived data and the glucose boundary.

In an embodiment of the first aspect, the on/off controller module isfurther configured to iteratively determine the insulin therapyinstruction in response to a host's metabolic response to an insulintherapy, wherein the on/off controller module comprises programmingconfigured to adjust an insulin delivery rate in response to the host'smetabolic response.

In an embodiment of the first aspect, the off insulin therapyinstruction is selected when the glucose concentration falls below theglucose boundary.

In an embodiment of the first aspect, the insulin delivery device isconfigured to automatically terminate insulin delivery in response toselection of the off insulin therapy instruction.

In an embodiment of the first aspect, the insulin delivery device isconfigured to provide delivery device data associated with insulindelivery.

In an embodiment of the first aspect, the internally derived datacomprises at least one of sensor data, processed sensor data, deliverydevice data, and processed delivery device data.

The integrated system of Claim 14, wherein the internally derived datafurther comprises at least one of a glucose concentration, a glucoseconcentration range, a change in glucose concentration, a glucoseconcentration rate of change, an acceleration of a glucose concentrationrate of change, a host insulin sensitivity, a change in host insulinsensitivity, a host metabolic response to insulin therapy, an amount ofinsulin delivered, a time of insulin delivery, an insulin on board, anda time.

In an embodiment of the first aspect, the integrated system furthercomprises an auxiliary sensor configured to provide auxiliary sensordata associated with at least one measurement made by the auxiliarysensor in the host, wherein the internally derived data furthercomprises auxiliary sensor data.

In an embodiment of the first aspect, the auxiliary sensor comprises atleast one of an accelerometer, a pressure sensor, a pH sensor, atemperature sensor, an oxygen sensor, an auxiliary glucose sensor, ananalyte sensor configured to measure an analyte other than glucose, aproximity sensor, and an orientation sensor.

In a second aspect, an integrated system for monitoring a glucoseconcentration in a host and for delivering insulin to a host isprovided, the system comprising a continuous glucose sensor, wherein thecontinuous glucose sensor is configured to substantially continuouslymeasure a glucose concentration in a host, and to provide sensor dataassociated with a glucose concentration of the host; an electronicsmodule comprising a basal controller module configured to iterativelydetermine an insulin therapy instruction in response to an evaluation ofa relationship of internally derived data and a basal profile, whereinthe basal profile comprises at least one time block associated with amaximum insulin delivery rate; and an insulin delivery device configuredto deliver insulin to the host, wherein the insulin delivery device isat least one of physically connected to a receiver and operablyconnected to a receiver, wherein the insulin delivery device isconfigured to receive the insulin therapy instruction from thecontroller module, wherein the insulin therapy instruction isconstrained by a maximum insulin delivery rate associated with a currenttime block.

In an embodiment of the second aspect, the insulin therapy instructionis determined solely on internally derived data and the basal profile.

In an embodiment of the second aspect, the maximum insulin delivery rateis an insulin delivery rate of from about 0.01 U/hour to about 6.0U/hour.

In an embodiment of the second aspect, the insulin delivery device isconfigured to deliver insulin automatically in response to receiving theinsulin therapy instruction.

In an embodiment of the second aspect, the insulin therapy instructioninstructs delivery of insulin at less than the maximum insulin deliveryrate associated with the current time block.

In an embodiment of the second aspect, the basal profile is programmableby at least one of the host and a caretaker of the host.

In an embodiment of the second aspect, the basal profile is programmableby at least one of the basal controller module and a manufacturer of theintegrated system.

In an embodiment of the second aspect, the basal controller module isconfigured to iteratively determine the insulin therapy instruction inresponse to internally derived data and the basal profile, wherein thebasal controller module comprises programming to adjust the basalprofile in response to internally derived data.

In an embodiment of the second aspect, the basal controller module isfurther configured to iteratively determine the insulin therapyinstruction in response to a host's metabolic response to an insulintherapy, wherein the basal controller module comprises programming toadjust the basal profile in response to the host's metabolic response.

In an embodiment of the second aspect, the insulin delivery device isconfigured to provide delivery device data associated with insulindelivery.

In an embodiment of the second aspect, the internally derived datacomprises at least one of sensor data, processed sensor data, deliverydevice data, and processed delivery device data.

In an embodiment of the second aspect, the internally derived datafurther comprises at least one of a glucose concentration, a glucoseconcentration range, a change in glucose concentration, a glucoseconcentration rate of change, an acceleration of the glucoseconcentration rate of change, a host insulin sensitivity, a change inhost insulin sensitivity, a host metabolic response to insulin therapy,an amount of insulin delivered, a time of insulin delivery, an insulinon board, and a time.

In an embodiment of the second aspect, the integrated system furthercomprises an auxiliary sensor configured to provide auxiliary sensordata associated with at least one measurement made by the auxiliarysensor in the host, wherein the internally derived data furthercomprises auxiliary sensor data.

In an embodiment of the second aspect, the auxiliary sensor comprises atleast one of an accelerometer, a pressure sensor, a pH sensor, atemperature sensor, an oxygen sensor, an auxiliary glucose sensor, ananalyte sensor configured to measure an analyte other than glucose, aproximity sensor, and an orientation sensor.

In a third embodiment, an integrated system for monitoring a glucoseconcentration in a host and for delivering insulin to a host isprovided, the system comprising a continuous glucose sensor, wherein thecontinuous glucose sensor is configured to substantially continuouslymeasure a glucose concentration in a host, and to provide sensor dataassociated with the glucose concentration of the host; an electronicsmodule comprising a bolus controller module configured to iterativelydetermine an insulin therapy instruction in response to an evaluation ofa relationship of internally derived data and an engageable bolusconstraint, wherein a relationship of internally derived data to thebolus constraint is evaluated in response to engagement of the bolusconstraint, and wherein the bolus constraint comprises a maximum totalinsulin dose that can be delivered within a predefined time period inresponse to engagement of the bolus constraint; and an insulin deliverydevice configured to deliver insulin to the host, wherein the insulindelivery device is at least one of physically connected to a receiverand operably connected to a receiver, wherein the insulin deliverydevice is configured to receive the insulin therapy from the controllermodule.

In an embodiment of the third aspect, the insulin therapy instruction isdetermined solely on internally derived data and the bolus constraint.

In an embodiment of the third aspect, the system further comprises atleast one of a selectable button configured to allow a user to engagethe engageable bolus constraint, a scroll wheel configured to allow auser to engage the engageable bolus constraint, and a menu selectionconfigured to allow a user to engage the engageable bolus constraint.

In an embodiment of the third aspect, the insulin therapy instructioncomprises an instruction to deliver a portion of the maximum totalinsulin dose.

In an embodiment of the third aspect, the insulin delivery device isconfigured to deliver insulin automatically in response to receiving theinsulin therapy instruction.

In an embodiment of the third aspect, the bolus constraint isprogrammable by as least one of the host and a caretaker of the host.

In an embodiment of the third aspect, the bolus constraint isprogrammable by as least one of the bolus controller module and amanufacturer of the integrated system.

In an embodiment of the third aspect, the bolus controller module isconfigured to iteratively determine an insulin therapy instruction inresponse to internally derived data and an engaged bolus constraint,wherein the bolus controller module comprises programming to adjust thebolus constraint in response to internally derived data.

In an embodiment of the third aspect, the bolus controller module isfurther configured to calculate insulin therapy in response to a host'smetabolic response to an insulin therapy, wherein the controller modulecomprises programming to adjust the bolus constraint in response to thehost's metabolic response.

In an embodiment of the third aspect, the insulin delivery device isconfigured to provide delivery device data associated with insulindelivery.

In an embodiment of the third aspect, the internally derived datacomprises at least one of sensor data, processed sensor data, deliverydevice data and processed delivery device data.

In an embodiment of the third aspect, the internally derived datafurther comprises at least one of a glucose concentration, a glucoseconcentration range, a change in glucose concentration, a glucoseconcentration rate of change, an acceleration of the glucoseconcentration rate of change, a host insulin sensitivity, a change inhost insulin sensitivity, a host metabolic response to insulin therapy,an amount of insulin delivered, a time of insulin delivery, an insulinon board, and a time.

In an embodiment of the third aspect, the integrated system furthercomprises an auxiliary sensor configured to provide auxiliary sensordata associated with at least one measurement taken by the auxiliarysensor in the host, wherein the internally derived data furthercomprises auxiliary sensor data.

In an embodiment of the third aspect, the auxiliary sensor comprises atleast one of an accelerometer, a pressure sensor, a pH sensor, atemperature sensor, an oxygen sensor, an auxiliary glucose sensor, ananalyte sensor configured to measure an analyte other than glucose, aproximity sensor, and an orientation sensor.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an integrated system of the preferredembodiments, including a continuous glucose sensor, a receiver forprocessing and displaying sensor data, a medicament delivery device, andan optional single point glucose-monitoring device.

FIG. 2A is a perspective view of a continuous glucose sensor in oneembodiment.

FIG. 2B is a perspective view of an in vivo portion of a transcutaneouscontinuous glucose sensor in one embodiment.

FIG. 2C is a cross-section of the portion of a transcutaneous continuousglucose sensor, of FIG. 2B, taken along line 2C-2C, in one embodiment.

FIG. 3 is a block diagram of the electronics associated with acontinuous glucose sensor in one embodiment.

FIG. 4 is a graph comparing the time-activity profiles of some exemplaryflash insulins (FI-1, FI2, FI3) to the time-activity profile of HumulinR, as taken from Frohnauer, et al. 2001, in “Graphical Human InsulinTime-Activity Profiles Using Standardized Definitions,” Diab. Tech. &Therap. 3(3):419-429.

FIGS. 5A and 5B are perspective views of an integrated system 10 in oneembodiment, wherein a receiver is integrated with a medicament deliverydevice in the form of a manual syringe, and optionally includes a singlepoint glucose monitor.

FIGS. 6A to 6C are perspective views of an integrated system in oneembodiment, wherein a receiver is integrated with a medicament deliverydevice in the form of one or more transdermal patches housed within aholder, and optionally includes a single point glucose monitor.

FIGS. 7A and 7B are perspective views of an integrated system in oneembodiment, wherein a receiver is integrated with a medicament deliverydevice in the form of a pen or jet-type injector, and optionallyincludes a single point glucose monitor.

FIGS. 8A to 8C are perspective views of an integrated system in oneembodiment, wherein a sensor and delivery pump, which are implanted ortransdermally inserted into the patient, are operably connected to anintegrated receiver, and optionally include a single point glucosemonitor.

FIG. 9 is a block diagram that illustrates integrated system electronicsin one embodiment.

FIG. 10 is a flow chart that illustrates the process of validatingtherapy instructions prior to medicament delivery in one embodiment.

FIG. 11 is a flow chart that illustrates the process of providingadaptive metabolic control using an integrated sensor and medicamentdelivery device in one embodiment.

FIG. 12 is a flow chart that illustrates the process of glucose signalestimation using the integrated sensor and medicament delivery device inone embodiment.

FIG. 13 is a flow chart that illustrates the process of determiningmedicament delivery in one embodiment.

FIG. 14 is a flow chart that illustrates the process of calculating amedicament therapy based on internally derived data in one embodiment.

FIG. 15 is a flow chart that illustrates the process of calculating amedicament therapy based on internally derived data, using an on/offcontroller module, in one embodiment.

FIG. 16 is a flow chart that illustrates the process of calculating amedicament therapy based on internally derived data, using a dynamicbasal controller module, in one embodiment.

FIG. 17 is a flow chart that illustrates the process of calculating amedicament therapy based on internally derived data, using a dynamicbolus module, in one embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

The following description and examples illustrate some exemplaryembodiments of the disclosed invention in detail. Those of skill in theart will recognize that there are numerous variations and modificationsof this invention that are encompassed by its scope. Accordingly, thedescription of a certain exemplary embodiment should not be deemed tolimit the scope of the present invention.

DEFINITIONS

In order to facilitate an understanding of the disclosed invention, anumber of terms are defined below.

The term “continuous glucose sensor,” as used herein is a broad term,and is to be given its ordinary and customary meaning to a person ofordinary skill in the art (and is not to be limited to a special orcustomized meaning), and refers without limitation to a device thatcontinuously or continually measures the glucose concentration of abodily fluid (e.g., blood, plasma, interstitial fluid and the like), forexample, at time intervals ranging from fractions of a second up to, forexample, 1, 2, or 5 minutes, or longer. It should be understood thatcontinual or continuous glucose sensors can continually measure glucoseconcentration without requiring user initiation and/or interaction foreach measurement, such as described with reference to U.S. Pat. No.6,001,067, for example.

The phrase “continuous glucose sensing,” as used herein is a broad term,and is to be given its ordinary and customary meaning to a person ofordinary skill in the art (and is not to be limited to a special orcustomized meaning), and refers without limitation to the period inwhich monitoring of the glucose concentration of a host's bodily fluid(e.g., blood, serum, plasma, extracellular fluid, etc.) is continuouslyor continually performed, for example, at time intervals ranging fromfractions of a second up to, for example, 1, 2, or 5 minutes, or longer.In one exemplary embodiment, the glucose concentration of a host'sextracellular fluid is measured every 1, 2, 5, 10, 20, 30, 40, 50 or60-seconds.

The term “biological sample,” as used herein is a broad term, and is tobe given its ordinary and customary meaning to a person of ordinaryskill in the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to sample of a host body, forexample, blood, interstitial fluid, spinal fluid, saliva, urine, tears,sweat, or the like.

The term “host,” as used herein as used herein is a broad term, and isto be given its ordinary and customary meaning to a person of ordinaryskill in the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to mammals such as humans.

The term “biointerface membrane,” as used herein is a broad term, and isto be given its ordinary and customary meaning to a person of ordinaryskill in the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to a permeable or semi-permeablemembrane that can include two or more domains and is typicallyconstructed of materials of a few microns thickness or more, which canbe placed over the sensing region to keep host cells (for example,macrophages) from gaining proximity to, and thereby damaging the sensingmembrane or forming a barrier cell layer and interfering with thetransport of glucose across the tissue-device interface.

The term “sensing membrane,” as used herein is a broad term, and is tobe given its ordinary and customary meaning to a person of ordinaryskill in the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to a permeable or semi-permeablemembrane that can be comprised of two or more domains and is typicallyconstructed of materials of a few microns thickness or more, which arepermeable to oxygen and are optionally permeable to glucose. In oneexample, the sensing membrane comprises an immobilized glucose oxidaseenzyme, which enables an electrochemical reaction to occur to measure aconcentration of glucose.

The term “domain,” as used herein is a broad term, and is to be givenits ordinary and customary meaning to a person of ordinary skill in theart (and is not to be limited to a special or customized meaning), andrefers without limitation to regions of a membrane that can be layers,uniform or non-uniform gradients (for example, anisotropic), functionalaspects of a material, or provided as portions of the membrane.

As used herein, the term “copolymer,” as used herein is a broad term,and is to be given its ordinary and customary meaning to a person ofordinary skill in the art (and is not to be limited to a special orcustomized meaning), and refers without limitation to polymers havingtwo or more different repeat units and includes copolymers, terpolymers,tetrapolymers, etc.

The term “sensing region,” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to the region of a monitoringdevice (e.g., an analyte sensor) responsible for the detection of aparticular analyte, such as but not limited to glucose. In oneembodiment, the sensing region generally comprises a non-conductivebody, a working electrode (anode), a reference electrode and a counterelectrode (cathode) passing through and secured within the body formingan electrochemically reactive surface at one location on the body and anelectronic connection at another location on the body, and a sensingmembrane affixed to the body and covering the electrochemically reactivesurface. The counter electrode typically has a greater electrochemicallyreactive surface area than the working electrode. During generaloperation of the sensor a biological sample (for example, blood orinterstitial fluid) or a portion thereof contacts (for example, directlyor after passage through one or more domains of the sensing membrane) anenzyme (for example, glucose oxidase, GOx); the reaction of thebiological sample (or portion thereof) results in the formation ofreaction products that allow a determination of the glucose level in thebiological sample. In one exemplary embodiment, the sensing regionincludes at least one working electrode and a second electrode, whichcan function as a reference and/or counter electrode. In anotherexemplary embodiment, the sensing region includes a plurality of workingelectrodes, a counter electrode and a reference electrode.

The term “electrochemically reactive surface,” as used herein is a broadterm, and is to be given its ordinary and customary meaning to a personof ordinary skill in the art (and is not to be limited to a special orcustomized meaning), and refers without limitation to the surface of anelectrode where an electrochemical reaction takes place. In the case ofthe working electrode, the hydrogen peroxide produced by the enzymecatalyzed reaction of the glucose being detected reacts creating ameasurable electronic current (for example, detection of glucoseutilizing glucose oxidase produces H₂O₂ as a by product, H₂O₂ reactswith the surface of the working electrode producing two protons (2H⁺),two electrons (2e⁻) and one molecule of oxygen (O₂) which produces theelectronic current being detected). In the case of the counterelectrode, a reducible species (for example, O₂) is reduced at theelectrode surface in order to balance the current being generated by theworking electrode.

The term “electrochemical cell,” as used herein is a broad term, and isto be given its ordinary and customary meaning to a person of ordinaryskill in the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to a device in which chemicalenergy is converted to electrical energy. Such a cell typically consistsof two or more electrodes held apart from each other and in contact withan electrolyte solution. Connection of the electrodes to a source ofdirect electric current renders one of them negatively charged and theother positively charged. Positive ions in the electrolyte migrate tothe negative electrode (cathode) and there combine with one or moreelectrons, losing part or all of their charge and becoming new ionshaving lower charge or neutral atoms or molecules; at the same time,negative ions migrate to the positive electrode (anode) and transfer oneor more electrons to it, also becoming new ions or neutral particles.The overall effect of the two processes is the transfer of electronsfrom the negative ions to the positive ions, a chemical reaction.

The term “proximal” as used herein is a broad term, and is to be givenits ordinary and customary meaning to a person of ordinary skill in theart (and is not to be limited to a special or customized meaning), andrefers without limitation to near to a point of reference such as anorigin or a point of attachment. For example, in some embodiments of asensing membrane that covers an electrochemically reactive surface, theelectrolyte domain is located more proximal to the electrochemicallyreactive surface than the interference domain.

The term “distal” as used herein is a broad term, and is to be given itsordinary and customary meaning to a person of ordinary skill in the art(and is not to be limited to a special or customized meaning), andrefers without limitation to spaced relatively far from a point ofreference, such as an origin or a point of attachment. For example, insome embodiments of a sensing membrane that covers an electrochemicallyreactive surface, a resistance domain is located more distal to theelectrochemically reactive surfaces than the enzyme domain.

The term “substantially” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to being largely but notnecessarily wholly that which is specified, which may include an amountgreater than 50 percent, an amount greater than 60 percent, an amountgreater than 70 percent, an amount greater than 80 percent, an amountgreater than 90 percent or more.

The terms “processor” and “processor module,” as used herein are a broadterms, and are to be given their ordinary and customary meaning to aperson of ordinary skill in the art (and are not to be limited to aspecial or customized meaning), and refer without limitation to acomputer system, state machine, processor, or the like designed toperform arithmetic or logic operations using logic circuitry thatresponds to and processes the basic instructions that drive a computer.In some embodiments, the terms can include ROM and/or RAM associatedtherewith.

The term “ROM,” as used herein is a broad term, and is to be given itsordinary and customary meaning to a person of ordinary skill in the art(and is not to be limited to a special or customized meaning), andrefers without limitation to read-only memory, which is a type of datastorage device manufactured with fixed contents. ROM is broad enough toinclude EEPROM, for example, which is electrically erasable programmableread-only memory (ROM).

The term “RAM,” as used herein is a broad term, and is to be given itsordinary and customary meaning to a person of ordinary skill in the art(and is not to be limited to a special or customized meaning), andrefers without limitation to a data storage device for which the orderof access to different locations does not affect the speed of access.RAM is broad enough to include SRAM, for example, which is static randomaccess memory that retains data bits in its memory as long as power isbeing supplied.

The term “A/D Converter,” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to hardware and/or software thatconverts analog electrical signals into corresponding digital signals.

The term “RF module,” as used herein is a broad term, and is to be givenits ordinary and customary meaning to a person of ordinary skill in theart (and is not to be limited to a special or customized meaning), andrefers without limitation to a radio frequency transmitter and/orreceiver for transmitting and/or receiving signals.

The terms “raw data stream” and “data stream,” as used herein are broadterms, and are to be given their ordinary and customary meaning to aperson of ordinary skill in the art (and are not to be limited to aspecial or customized meaning), and refer without limitation to ananalog or digital signal directly related to the analyte concentrationmeasured by the analyte sensor. In one example, the raw data stream isdigital data in “counts” converted by an A/D converter from an analogsignal (for example, voltage or amps) representative of an analyteconcentration. The terms broadly encompass a plurality of time spaceddata points from a substantially continuous analyte sensor, whichcomprises individual measurements taken at time intervals ranging fromfractions of a second up to, for example, 1, 2, or 5 minutes or longer.

The term “counts,” as used herein is a broad term, and is to be givenits ordinary and customary meaning to a person of ordinary skill in theart (and is not to be limited to a special or customized meaning), andrefers without limitation to a unit of measurement of a digital signal.In one example, a raw data stream measured in counts is directly relatedto a voltage (for example, converted by an A/D converter), which isdirectly related to current from a working electrode.

The term “electronic circuitry,” as used herein is a broad term, and isto be given its ordinary and customary meaning to a person of ordinaryskill in the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to the components (for example,hardware and/or software) of a device configured to process data. In thecase of an analyte sensor, the data includes biological informationobtained by a sensor regarding the concentration of the analyte in abiological fluid. U.S. Pat. Nos. 4,757,022, 5,497,772 and 4,787,398,which are hereby incorporated by reference in their entirety, describesuitable electronic circuits that can be utilized with devices ofcertain embodiments.

The term “potentiostat,” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to an electrical system thatcontrols the potential between the working and reference electrodes of athree-electrode cell at a preset value. The potentiostat forces whatevercurrent is necessary to flow between the working and counter electrodesto keep the desired potential, as long as the needed cell voltage andcurrent do not exceed the compliance limits of the potentiostat.

The terms “operably connected” and “operably linked,” as used herein arebroad terms, and are to be given their ordinary and customary meaning toa person of ordinary skill in the art (and are not to be limited to aspecial or customized meaning), and refer without limitation to one ormore components being linked to another component(s) in a manner thatallows transmission of signals between the components. For example, oneor more electrodes can be used to detect the amount of glucose in asample and convert that information into a signal; the signal can thenbe transmitted to an electronic circuit. In this case, the electrode is“operably linked” to the electronic circuit. These terms are broadenough to include wired and wireless connectivity.

The term “algorithmically smoothed,” as used herein is a broad term, andis to be given its ordinary and customary meaning to a person ofordinary skill in the art (and is not to be limited to a special orcustomized meaning), and refers without limitation to modification of aset of data to make it smoother and more continuous and remove ordiminish outlying points, for example, by performing a moving average ofthe raw data stream.

The term “algorithm,” as used herein is a broad term, and is to be givenits ordinary and customary meaning to a person of ordinary skill in theart (and is not to be limited to a special or customized meaning), andrefers without limitation to the computational processes (for example,programs) involved in transforming information from one state toanother, for example using computer processing.

The term “regression,” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to finding a line in which a setof data has a minimal measurement (for example, deviation) from thatline. Regression can be linear, non-linear, first order, second order,and so forth. One example of regression is least squares regression.

The terms “recursive filter” and “auto-regressive algorithm,” as usedherein are broad terms, and are to be given their ordinary and customarymeaning to a person of ordinary skill in the art (and are not to belimited to a special or customized meaning), and refer withoutlimitation to an equation in which previous averages are part of thenext filtered output. More particularly, the generation of a series ofobservations whereby the value of each observation is partly dependenton the values of those that have immediately preceded it. One example isa regression structure in which lagged response values assume the roleof the independent variables.

The terms “velocity” and “rate of change,” as used herein are broadterms, and are to be given their ordinary and customary meaning to aperson of ordinary skill in the art (and are not to be limited to aspecial or customized meaning), and refer without limitation to timerate of change; the amount of change divided by the time required forthe change. In one embodiment, these terms refer to the rate of increaseor decrease in an analyte for a certain time period.

The term “acceleration” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to the rate of change ofvelocity with respect to time. This term is broad enough to includedeceleration.

The term “clinical risk,” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to an identified danger orpotential risk to the health of a host based on a measured or estimatedanalyte concentration, its rate of change, and/or its acceleration.

The term “clinically acceptable,” as used herein is a broad term, and isto be given its ordinary and customary meaning to a person of ordinaryskill in the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to an analyte concentration,rate of change, and/or acceleration associated with that measuredanalyte that is considered to be safe for a host.

The term “time period,” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to an amount of time including asingle point in time and a path (for example, range of time) thatextends from a first point in time to a second point in time.

The term “measured analyte values,” as used herein is a broad term, andis to be given its ordinary and customary meaning to a person ofordinary skill in the art (and is not to be limited to a special orcustomized meaning), and refers without limitation to an analyte valueor set of analyte values for a time period for which analyte data hasbeen measured by an analyte sensor. The term is broad enough to includedata from the analyte sensor before or after data processing in thesensor and/or receiver (for example, data smoothing, calibration, or thelike).

The term “alarm,” as used herein is a broad term, and is to be given itsordinary and customary meaning to a person of ordinary skill in the art(and is not to be limited to a special or customized meaning), andrefers without limitation to audible, visual, or tactile signal that aretriggered in response to detection of clinical risk to a host. In oneembodiment, hyperglycemic and hypoglycemic alarms are triggered whenpresent or future clinical danger is assessed based on continuousanalyte data.

The term “computer,” as used herein is a broad term, and is to be givenits ordinary and customary meaning to a person of ordinary skill in theart (and is not to be limited to a special or customized meaning), andrefers without limitation to a machine that can be programmed tomanipulate data.

The term “modem,” as used herein is a broad term, and is to be given itsordinary and customary meaning to a person of ordinary skill in the art(and is not to be limited to a special or customized meaning), andrefers without limitation to an electronic device for converting betweenserial data from a computer and an audio signal suitable fortransmission over a telecommunications connection to another modem.

The term “intelligent,” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to systems and methodsprogrammed to be able to adjust to changes in the current conditions andmake deductions from information being processed.

The term “adaptive,” as used herein is a broad term, and is to be givenits ordinary and customary meaning to a person of ordinary skill in theart (and is not to be limited to a special or customized meaning), andrefers without limitation to an ability (e.g., systems and methods ableto) to be adjusted for use in different conditions; to change somethingto suit different conditions. In some embodiments, an adaptivecontroller module can be configured to adjust the medicament deliveryrate, the medicament volume, the time of delivery, and the like, basedon evaluation of internally derived data and the host metabolic responseto therapy.

The term “condition,” as used herein is a broad term, and is to be givenits ordinary and customary meaning to a person of ordinary skill in theart (and is not to be limited to a special or customized meaning), andrefers without limitation to a mode or state of being; the physicalstatus of the body as a whole or of one of its parts. For example, ahost's condition can refer to his state of health, his metabolic stateand the like.

The term “glucose boundary,” as used herein is a broad term, and is tobe given its ordinary and customary meaning to a person of ordinaryskill in the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to a glucose concentration orrange of glucose concentrations. In some embodiments, the system isconfigured to compare and/or evaluate internally derived data with aglucose boundary. In some embodiments, a glucose boundary can include amaximum glucose concentration.

The term “on/off controller module,” as used herein is a broad term, andis to be given its ordinary and customary meaning to a person ofordinary skill in the art (and is not to be limited to a special orcustomized meaning), and refers without limitation to a mechanismconfigured to select between two instructions, namely either “on” or“off” An on/off controller module can include a device, such as aswitch, programming or a combination thereof, that can actuate and/orde-actuate an insulin delivery device, such that the device is eitherdelivering insulin or not delivering insulin. In some embodiments, theon instruction is sent to the insulin delivery device, which isconfigured to deliver the insulin, such as to automatically deliver theinsulin; similarly, the off instruction can be sent to the insulindelivery device, which terminates insulin delivery upon receipt of theoff instruction.

The term “basal,” as used herein is a broad term, and is to be given itsordinary and customary meaning to a person of ordinary skill in the art(and is not to be limited to a special or customized meaning), andrefers without limitation to the minimum required rate or other valuefor something to function. For example, in the case of insulin therapy,the term “basal rate” can refer to a regular (e.g., in accordance withfixed order or procedure, such as regularly scheduled for/at a fixedtime), periodic or continuous delivery of low levels of insulin, such asbut not limited to throughout a 24-hour period.

The term “basal profile,” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to an insulin delivery schedulethat includes one or more blocks of time (e.g., time blocks), whereineach block is associated with a maximum insulin delivery rate.

The term “dynamic basal controller module,” as used herein is a broadterm, and is to be given its ordinary and customary meaning to a personof ordinary skill in the art (and is not to be limited to a special orcustomized meaning), and refers without limitation to a controllermodule configured to intelligently and adaptively evaluate internallyderived data relative to a basal profile and to determine a basalinsulin therapy (e.g., an insulin delivery rate) based thereon, whereinthe insulin therapy can include a delivery rate of up to the maximumdelivery rate associated with a time block of the basal profile.

The term “bolus,” as used herein is a broad term, and is to be given itsordinary and customary meaning to a person of ordinary skill in the art(and is not to be limited to a special or customized meaning), andrefers without limitation to a single dose of insulin, usually givenover a short, defined period of time, that has been calculated and/orestimated to be sufficient to cover an expected rise in blood glucose,such as the rise that generally occurs during/after a meal.

The term “bolus constraint,” as used herein is a broad term, and is tobe given its ordinary and customary meaning to a person of ordinaryskill in the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to an engageable (e.g.,selectable) maximum total insulin therapy (e.g., maximum total dose)that can be delivered during a defined period of time. In someembodiments, the bolus constraint has been calculated/estimated to besufficient to cover an expected rise in glucose, such as an averageglucose increase associate with consumption of a meal. In someembodiments, the host, a caretaker of the host, and/or the manufacturercan program a bolus constraint. In some circumstances, a bolusconstraint can be programmed by an intelligent/adaptive controllermodule.

The term “dynamic bolus controller module,” as used herein is a broadterm, and is to be given its ordinary and customary meaning to a personof ordinary skill in the art (and is not to be limited to a special orcustomized meaning), and refers without limitation to a controllermodule configured to intelligently and adaptively evaluate internallyderived data against (e.g., relative to) an engaged bolus constraint andto calculate an therapy based thereon, wherein the calculations areconstrained by the engaged bolus constraint. A dynamic bolus controllermodule can include one or more instructions for calculation and/ordelivery of a dynamic basal insulin therapy, such as but not limited toinstructions to the insulin delivery device to delivery the bolustherapy automatically.

The term “range,” as used herein is a broad term, and is to be given itsordinary and customary meaning to a person of ordinary skill in the art(and is not to be limited to a special or customized meaning), andrefers without limitation to a sequence, series, or scale between limits(e.g., maximum and minimum values). For example, a range of glucoseconcentrations can include glucose concentrations from 60 mg/dl to 200mg/dl. In another example, a range of insulin delivery rates can includerates from about 0.01 U/hr to about 40 U/hr. In some embodiments, arange is a single value.

The terms “programmed” and “programmable,” as used herein are broadterms, and are to be given their ordinary and customary meaning to aperson of ordinary skill in the art (and are not to be limited to aspecial or customized meaning), and refer without limitation to being orable to be arranged, as in a series of steps and/or instructions to becarried out, such as by a computer. As used herein, the terms programmedand programmable includes “pre-programmed,” “pre-programmable,”“re-programmed” and “re-programmable.” In one example, a constraint canbe programmed prior to use and/or reprogrammed at a later time.

The term “internally derived data,” as used herein is a broad term, andis to be given its ordinary and customary meaning to a person ofordinary skill in the art (and is not to be limited to a special orcustomized meaning), and refers without limitation to data measuredand/or processed by the integrated system, or a component thereof.Internally derived data can include data from a system component, suchas but not limited to an analyte sensor (e.g., continuous glucosesensor), an auxiliary sensor, and/or an insulin delivery device.Internally derived data can include data derived (e.g., by processingand/or algorithmic evaluation) from the data received from a systemcomponent, such as but not limited to processed data, evaluated rawand/or processed data, host insulin sensitivity, host metabolicresponse, relationship of insulin sensitivity and/or metabolic responseto each other, time, activity level, tracking of internally derived datato establish trends, insulin delivered and/or on-board, and the like. Insome circumstances, internally derived data can include older and/or newdata, such as but not limited to data received in the past (e.g.,minutes, hours, days, weeks or months) and/or recently received data(e.g., currently received, instant, such as but not limited to withinthe previous 1-15 minutes). In some embodiments, a controller module canevaluate the internally derived data as it is received.

The term “insulin therapy,” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to an amount and/or schedule ofthe insulin to be delivered to the host. An insulin therapy can includeone or more doses of insulin, up to the maximum (e.g., dose, therapy)associated with a constraint, such as but not limited to a basal profileand/or a bolus constraint. In some circumstances, the insulin therapycalculated and/or delivered can include a one or more partial doses thatsum to an amount less than or equal to the maximum (e.g., dose, therapy)associated with a constraint. In some circumstances, the user canoverride the insulin therapy calculated by a controller module and/orassociated with a constraint, such as, for example, to command theintegrated system to deliver a manually entered insulin therapy.

The term “target range,” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to a range of glucoseconcentrations within which a host is to try to maintain his bloodsugar. In general, a target range is a range of glucose concentrationsconsidered to be euglycemic. Euglycemic glucose concentrations arediscussed in detail in the section entitled “Programming andProcessing.”

The term “meal,” as used herein is a broad term, and is to be given itsordinary and customary meaning to a person of ordinary skill in the art(and is not to be limited to a special or customized meaning), andrefers without limitation to an amount of food or beverage consumed bythe host. In some circumstances, a meal is associated with a time ofday, during which that meal is generally consumed, such as but notlimited to breakfast, lunch, dinner, supper, snack, and the like. Insome circumstances, a meal is associated with a particular type of foodor beverage, such as one that a host consumes only occasionally, such asbut not limited to a high fat meal (e.g., pizza) or a high carbohydratemeal (e.g., cake, cookies, candy, ice cream, and the like).

The term “auxiliary sensor,” as used herein is a broad term, and is tobe given its ordinary and customary meaning to a person of ordinaryskill in the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to a sensor other than thecontinuous glucose sensor, which is configured to sense glucose or ananalyte other than glucose, or to sense a condition, such as but notlimited to temperature, pH, host activity level, orientation, pressure,proximity and the like.

Overview

FIG. 1 is a block diagram of an integrated system 10 of the preferredembodiments, including a continuous glucose sensor 12, a receiver 14 forprocessing and displaying sensor data, a medicament delivery device 16,and optionally a single point glucose-monitoring device 18. Theintegrated diabetes management system 10 of the preferred embodimentsprovides improved convenience and accuracy thus affording a diabetichost 8 with improved convenience, functionality, and safety in the careof their disease.

FIG. 1 shows a continuous glucose sensor 12 that measures aconcentration of glucose or a substance indicative of the concentrationor presence of the glucose. In some embodiments, the glucose sensor 12is an invasive, minimally invasive, or non-invasive device, for examplea subcutaneous, transdermal, intravascular or extracorporeal device. Insome embodiments, the sensor 12 can analyze a plurality of intermittentbiological samples. The glucose sensor can use any method ofglucose-measurement, including enzymatic, chemical, physical,electrochemical, spectrophotometric, polarimetric, calorimetric,radiometric, or the like. In alternative embodiments, the sensor 12 canbe any sensor capable of determining the level of an analyte in thebody, for example oxygen, lactase, insulin, hormones, cholesterol,medicaments, viruses, or the like. The glucose sensor 12 uses any knownmethod to provide an output signal indicative of the concentration ofthe glucose. The output signal is typically a raw data stream that isused to provide a useful value of the measured glucose concentration toa host or doctor, for example.

Accordingly, a receiver 14 is provided that receives and processes theraw data stream, including calibrating, validating, and displayingmeaningful glucose values to a host, such as described in more detailbelow. A medicament delivery device 16 is further provided as a part ofthe integrated system 10. In some embodiments, the medicament deliverydevice 16 is a manual delivery device, for example a syringe, inhaler,or transdermal patch, which is manually integrated with the receiver 14.In some embodiments, the medicament delivery device 16 is asemi-automated delivery device, for example a pen or jet-type injector,an inhaler, a spray, or pump, which provides a semi-automatedintegration with the receiver 14. In some embodiments, the medicamentdelivery device 16 is an automated delivery device, for example atranscutaneous or implantable pump system, which provides an automatedintegration with the receiver 14. In some embodiments, an optionalsingle point glucose monitor 18 is further provided as a part of theintegrated system 10, for example a self-monitoring blood glucose meter(SHBG), non-invasive glucose meter, or the like.

Conventionally, each of these devices separately provides valuableinformation and or services to diabetic hosts. Thus, a typical diabetichost has numerous individual devices, which they track and considerseparately. In some cases, the amount of information provided by theseindividual devices may require complex understanding of the nuances andimplications of each device, for example types and amounts of insulin todeliver. Typically, each individual device is a silo of information thatfunctions as well as the data provided therein, therefore when thedevices are able to communicate with each other, enhanced functionalityand safety can be realized. For example, when a continuous glucosemonitor functions alone (for example, without data other than that whichwas gathered by the device), sudden changes in glucose level aretracked, but may not be fully understood, predicted, preempted, orotherwise considered in the processing of the sensor data; however, ifthe continuous glucose sensor were provided with information about time,amount, and type of insulin injections, calories consumed, time or day,meal time, or like, more meaningful, accurate and useful glucoseestimation, prediction, and other such processing can be provided, suchas described in more detail herein. By integrating these devices, theinformation from each component can be leveraged to increase theintelligence, benefit provided, convenience, safety, and functionalityof the continuous glucose sensor and other integrated components.Therefore, it would be advantageous to provide a device that aids thediabetic host in integrating these individual devices in the treatmentof his/her disease.

In the non-diabetic host, pancreatic β-cells generally respond quicklyto spikes in blood glucose by releasing stored insulin (e.g., withinabout 10-minutes). In preferred embodiments, the integrated system 10 isconfigured to mimic pancreatic β-cells, and thereby to providesubstantially physiological detection of glucose levels and/or insulinresponse. Accordingly, the system 10 includes a continuous analytesensor, a medicament delivery device (e.g., an infusion pump, a pen, asyringe, an inhaler, a medicament patch, and the like), and associatedelectronics, as described elsewhere herein. In various embodiments, theelectronics include one or more of an on/off controller module, adynamic basal controller module and/or a dynamic bolus controllermodule, as described elsewhere herein. In some embodiments, theelectronics include two or more controller modules configured to work inconcert. The system 10 is configured for use with regular, rapid-acting,fast-acting and/or flash-acting insulins, which are described elsewhereherein. In one exemplary embodiment, the system 10 is configured todetermine a medicament dose (e.g., an insulin dose) using solelyinternally derived data.

Glucose Sensor

FIG. 2A is a perspective view of one embodiment of a wholly implantablecontinuous glucose sensor 12 (e.g., the primary analyte sensor). In thisembodiment, a body 20 and a sensing region 22 house the electrodes andsensor electronics (FIG. 3). The three electrodes within the sensingregion are operably connected to the sensor electronics (FIG. 3) and arecovered by a sensing membrane and a biointerface membrane (not shown),which are described in more detail below.

The body 20 is preferably formed from epoxy molded around the sensorelectronics, however the body can be formed from a variety of materials,including metals, ceramics, plastics, or composites thereof. U.S. Pat.No. 7,134,999 discloses suitable configurations suitable for the body20, and is incorporated by reference in its entirety.

In one embodiment, the sensing region 22 comprises three electrodesincluding a platinum working electrode, a platinum counter electrode,and a silver/silver chloride reference electrode, for example. However avariety of electrode materials and configurations can be used with theimplantable glucose sensor of the preferred embodiments. The top ends ofthe electrodes are in contact with an electrolyte phase (not shown),which is a free-flowing fluid phase disposed between the sensingmembrane and the electrodes. In one embodiment, the counter electrode isprovided to balance the current generated by the species being measuredat the working electrode. In the case of a glucose oxidase based glucosesensor, the species being measured at the working electrode is H₂O₂.Glucose oxidase catalyzes the conversion of oxygen and glucose tohydrogen peroxide and gluconate according to the following reaction:

Glucose+O₂→Gluconate+H₂O₂

The change in H₂O₂ can be monitored to determine glucose concentrationbecause for each glucose molecule metabolized, there is a proportionalchange in the product H₂O₂. Oxidation of H₂O₂ by the working electrodeis balanced by reduction of ambient oxygen, enzyme generated H₂O₂, orother reducible species at the counter electrode. The H₂O₂ produced fromthe glucose oxidase reaction further reacts at the surface of workingelectrode and produces two protons (2H⁺), two electrons (2e⁻), and oneoxygen molecule (O₂).

In one embodiment, a potentiostat (FIG. 3) is employed to monitor theelectrochemical reaction at the electroactive surface(s). Thepotentiostat applies a constant potential to the working and referenceelectrodes to determine a current value. The current that is produced atthe working electrode (and flows through the circuitry to the counterelectrode) is substantially proportional to the amount of H₂O₂ thatdiffuses to the working electrode. Accordingly, a raw signal can beproduced that is representative of the concentration of glucose in theuser's body, and therefore can be utilized to estimate a meaningfulglucose value.

In some embodiments, the sensing membrane includes an enzyme, forexample, glucose oxidase, and covers the electrolyte phase. In oneembodiment, the sensing membrane generally includes a resistance domainmost distal from the electrochemically reactive surfaces, an enzymedomain less distal from the electrochemically reactive surfaces than theresistance domain, and an electrolyte domain adjacent to theelectrochemically reactive surfaces. However, it is understood that asensing membrane modified for other devices, for example, by includingfewer or additional domains, is within the scope of the preferredembodiments. U.S. Patent Publication No. US-2003-0032874-A1 describesmembranes that can be used in some embodiments of the sensing membrane.It is noted that in some embodiments, the sensing membrane canadditionally include an interference domain that blocks some interferingspecies; such as described in the above-cited co-pending patentapplication. U.S. Patent Publication No. US-2005-0090607-A1 alsodescribes membranes that can be used for the sensing membrane of thepreferred embodiments, and is incorporated herein by reference in itsentirety.

Preferably, the biointerface membrane supports tissue ingrowth, servesto interfere with the formation of a barrier cell layer, and protectsthe sensitive regions of the device from host inflammatory response. Inone embodiment, the biointerface membrane generally includes a celldisruptive domain most distal from the electrochemically reactivesurfaces and a cell impermeable domain less distal from theelectrochemically reactive surfaces than the cell disruptive domain. Thecell disruptive domain is preferably designed to support tissueingrowth, disrupt contractile forces typically found in a foreign bodyresponse, encourage vascularity within the membrane, and disrupt theformation of a barrier cell layer. The cell impermeable domain ispreferably resistant to cellular attachment, impermeable to cells, andcomposed of a biostable material. U.S. Pat. No. 6,702,857, U.S. Pat. No.7,192,450, and U.S. Patent Publication No. US-2005-0251083-A1 describebiointerface membranes that can be used in conjunction with thepreferred embodiments, and are incorporated herein by reference in theirentirety. It is noted that the preferred embodiments can be used with ashort term (for example, 1 to 7 day sensor), in which case abiointerface membrane may not be required. It is noted that thebiointerface membranes described herein provide a continuous glucosesensor that has a useable life of greater than about one week, greaterthan about one month, greater than about three months, or greater thanabout one year, herein after referred to as “long-term.”

In some embodiments, the domains of the biointerface and sensingmembranes are formed from materials such as silicone,polytetrafluoroethylene, polyethylene-co-tetrafluoroethylene,polyolefin, polyester, polycarbonate, biostable polytetrafluoroethylene,homopolymers, copolymers and/or terpolymers of polyurethanes,polypropylene (PP), polyvinylchloride (PVC), polyvinylidene fluoride(PVDF), polybutylene terephthalate (PBT), polymethylmethacrylate (PMMA),polyether ether ketone (PEEK), polyurethanes, cellulosic polymers,polysulfones and block copolymers thereof including, for example,di-block, tri-block, alternating, random and graft copolymers.

FIG. 2B is a perspective view of an in vivo portion of a transcutaneouscontinuous glucose sensor 12, in one embodiment. In this embodiment, thein vivo portion of the sensor includes at least one working electrode 12a and a reference electrode 12 b and a sensing membrane 12 c.

FIG. 2C is a cross-section of the sensor shown in FIG. 2B, taken on line2C-2C. In preferred embodiments, the sensing membrane 12 c (e.g., abiointerface and/or sensing membrane) includes at least an enzyme domain12 f having an enzyme configured to detect the analyte, such as but notlimited to glucose oxidase, as described elsewhere herein. In somepreferred embodiments, the sensing membrane 12 c can include one or moreadditional domains, such as but not limited to an electrode domain 12 d,an interference domain 12 e, a resistance domain 12 j, a cell disruptivedomain and a cell impermeable domain, for example. Additional sensor andsensing membrane configurations can be found in U.S. Patent PublicationNo. US-2006-0020187-A1, U.S. Patent Publication No. US-2005-0031689-A1,U.S. Patent Publication No. 2007-0027370-A1, U.S. Patent Publication No.2006-0229512-A1, U.S. Patent Publication No. 2006-0253012-A1, U.S.Patent Publication No. US-2007-0197890-A1, U.S. application Ser. No.11/404,417 filed on Apr. 14, 2006 and entitled “SILICONE BASED MEMBRANESFOR USE IN IMPLANTABLE GLUCOSE SENSORS,” and U.S. application Ser. No.11/750,907 filed on May 18, 2007 and entitled “ANALYTE SENSORS HAVING ANOPTIMIZED SIGNAL-TO-NOISE RATIO,” each of which is incorporated hereinby reference in its entirety.

In preferred embodiments, the analyte sensor 12 is configured to provideresponse to changes in host glucose concentration, such as but notlimited to a sensor response time of about 20-minutes or less. The term“sensor response time” as used herein is a broad term, and is to begiven its ordinary and customary meaning to a person of ordinary skillin the art (and is not to be limited to a special or customizedmeaning), and refers without limitation to the time required for thesensor to measure a stable signal value associated with a change inglucose concentration, from a first concentration to a secondconcentration. The sensor response time can be measured by in vitroexperimentation. For example, sensor response time can be measured byfirst placing a continuous glucose sensor in a first glucose solution(e.g., 100 mg/dl glucose); then moving the sensor to a second glucosesolution (e.g., 200 mg/dl glucose) and allowing the sensor toequilibrate. In some embodiments, the sensor response time is less thanabout 10-minutes. In preferred embodiments, the sensor response time isless than 1, 2, 3, 4, or 5-minutes. In more preferred embodiments, thesensor response time is less than about 30-seconds. In some alternativeembodiments, sensor response time includes an additional period of timerequired to process the measured glucose concentration change andprovide a numerical output to the user (e.g., via a receiver).

FIG. 3 is a block diagram that illustrates the electronics associatedwith a continuous glucose sensor 12 in one embodiment. In thisembodiment, a potentiostat 24 is shown, operably connected to anelectrode system (such as described above) and provides a voltage to theelectrodes (FIG. 2), which biases the sensor to enable measurement of acurrent signal indicative of the analyte concentration in the host (alsoreferred to as the analog portion). In some embodiments, thepotentiostat includes a resistor (not shown) that translates the currentinto voltage. In some alternative embodiments, a current to frequencyconverter is provided that is configured to continuously integrate themeasured current, for example, using a charge counting device. An A/Dconverter 26 digitizes the analog signal into a digital signal, alsoreferred to as “counts” in some embodiments for processing. Accordingly,the resulting raw data stream in counts, also referred to as raw sensordata, is directly related to the current measured by the potentiostat24.

A processor module 28 includes the central control unit (houses ROM 30and RAM 32) that controls the processing of the sensor electronics. Insome embodiments, the processor module includes a microprocessor,however a computer system other than a microprocessor can be used toprocess data as described herein, for example an ASIC can be used forsome or all of the sensor's central processing. The processor typicallyprovides semi-permanent storage of data, for example, storing data suchas sensor identifier (ID) and programming to process data streams (forexample, programming for data smoothing and/or replacement of signalartifacts such as is described in U.S. Publication No.US-2005-0043598-A1). The processor additionally can be used for thesystem's cache memory, for example for temporarily storing recent sensordata. In some embodiments, the processor module comprises memory storagecomponents such as ROM 30, RAM 32, dynamic-RAM, static-RAM, non-staticRAM, EEPROM, rewritable ROMs, flash memory, or the like.

In some embodiments, the processor module comprises a digital filter,for example, an infinite impulse response (IIR) or finite impulseresponse (FIR) filter, configured to smooth the raw data stream from theA/D converter. Generally, digital filters are programmed to filter datasampled at a predetermined time interval (also referred to as a samplerate). In some embodiments, wherein the potentiostat is configured tomeasure the analyte at discrete time intervals, these time intervalsdetermine the sample rate of the digital filter. In some alternativeembodiments, wherein the potentiostat is configured to continuouslymeasure the analyte, for example, using a current-to-frequency converteras described above, the processor module can be programmed to request adigital value from the A/D converter at a predetermined time interval,also referred to as the acquisition time. In these alternativeembodiments, the values obtained by the processor are advantageouslyaveraged over the acquisition time due the continuity of the currentmeasurement. Accordingly, the acquisition time determines the samplerate of the digital filter. In preferred embodiments, the processormodule is configured with a programmable acquisition time, namely, thepredetermined time interval for requesting the digital value from theA/D converter is programmable by a user within the digital circuitry ofthe processor module. An acquisition time of from about 2 seconds toabout 512 seconds is preferred; however any acquisition time can beprogrammed into the processor module. A programmable acquisition time isadvantageous in optimizing noise filtration, time lag, andprocessing/battery power.

Preferably, the processor module 28 is configured to build the datapacket for transmission to an outside source, for example, a RadioFrequency (RF) transmission (e.g., via RF module 38) to a receiver asdescribed in more detail below. Generally, the data packet comprises aplurality of bits that can include a preamble, a unique identifieridentifying the electronics unit, the receiver, or both, (e.g., sensorID code), data (e.g., raw data, filtered data, and/or an integratedvalue) and/or error detection or correction. Preferably, the data(transmission) packet has a length of from about 8 bits to about 128bits, preferably about 48 bits; however, larger or smaller packets canbe desirable in certain embodiments. The processor module 28 can beconfigured to transmit any combination of raw and/or filtered data. Inone exemplary embodiment, the transmission packet contains a fixedpreamble, a unique ID of the electronics unit, a single five-minuteaverage (e.g., integrated) sensor data value, and a cyclic redundancycode (CRC).

In some embodiments, the processor module 28 further comprises atransmitter portion that determines the transmission interval of thesensor data to a receiver, or the like. In some embodiments, thetransmitter portion, which determines the interval of transmission, isconfigured to be programmable. In one such embodiment, a coefficient canbe chosen (e.g., a number of from about 1 to about 100, or more),wherein the coefficient is multiplied by the acquisition time (orsampling rate), such as described above, to define the transmissioninterval of the data packet. Thus, in some embodiments, the transmissioninterval is programmable from about 2 seconds to about 850 minutes, morepreferably from about 30 second to about 5 minutes; however, anytransmission interval can be programmable or programmed into theprocessor module. However, a variety of alternative systems and methodsfor providing a programmable transmission interval can also be employed.By providing a programmable transmission interval, data transmission canbe customized to meet a variety of design criteria (e.g., reducedbattery consumption, timeliness of reporting sensor values, etc.).

Conventional glucose sensors measure current in the nanoAmp range. Incontrast to conventional glucose sensors, the preferred embodiments areconfigured to measure the current flow in the picoAmp range, and in someembodiments, femtoAmps. Namely, for every unit (mg/dL) of glucosemeasured, at least one picoAmp of current is measured. Preferably, theanalog portion of the A/D converter 26 is configured to continuouslymeasure the current flowing at the working electrode and to convert thecurrent measurement to digital values representative of the current. Inone embodiment, the current flow is measured by a charge counting device(e.g., a capacitor). Preferably, a charge counting device provides avalue (e.g., digital value) representative of the current flowintegrated over time (e.g., integrated value). In some embodiments, thevalue is integrated over a few seconds, a few minutes, or longer. In oneexemplary embodiment, the value is integrated over 5 minutes; however,other integration periods can be chosen. Thus, a signal is provided,whereby a high sensitivity maximizes the signal received by a minimalamount of measured hydrogen peroxide (e.g., minimal glucose requirementswithout sacrificing accuracy even in low glucose ranges), reducing thesensitivity to oxygen limitations in vivo (e.g., in oxygen-dependentglucose sensors).

In some embodiments, the electronics unit is programmed with a specificID, which is programmed (automatically or by the user) into a receiverto establish a secure wireless communication link between theelectronics unit and the receiver. Preferably, the transmission packetis Manchester encoded; however, a variety of known encoding techniquescan also be employed.

A battery 34 is operably connected to the sensor electronics andprovides the power for the sensor 12. In one embodiment, the battery isa lithium manganese dioxide battery; however, any appropriately sizedand powered battery can be used (for example, AAA, nickel-cadmium,zinc-carbon, alkaline, lithium, nickel-metal hydride, lithium-ion,zinc-air, zinc-mercury oxide, silver-zinc, and/or hermetically-sealed).In some embodiments, the battery is rechargeable, and/or a plurality ofbatteries can be used to power the system. The sensor can betranscutaneously powered via an inductive coupling, for example. In someembodiments, a quartz crystal 36 is operably connected to the processor28 and maintains system time for the computer system as a whole, forexample for the programmable acquisition time within the processormodule.

An RF module 38 is operably connected to the processor 28 and transmitsthe sensor data from the sensor 12 to a receiver within a wirelesstransmission 40 via antenna 42. In some embodiments, a second quartzcrystal 44 provides the time base for the RF carrier frequency used fordata transmissions from the RF module 38. In some alternativeembodiments, however, other mechanisms, such as optical, infraredradiation (IR), ultrasonic, or the like, can be used to transmit and/orreceive data.

In the RF telemetry module of the preferred embodiments, the hardwareand software are designed for low power requirements to increase thelongevity of the device (for example, to enable a life of from about 3to about 24 months, or more) with maximum RF transmittance from the invivo environment to the ex vivo environment for wholly implantablesensors (for example, a distance of from about one to ten meters ormore). Preferably, a high frequency carrier signal of from about 402 MHzto about 433 MHz is employed in order to maintain lower powerrequirements. In some embodiments, the RF module employs a one-way RFcommunication link to provide a simplified ultra low power datatransmission and receiving scheme. The RF transmission can be OOK or FSKmodulated, preferably with a radiated transmission power (EIRP) fixed ata single power level of typically less than about 100 microwatts,preferably less than about 75 microwatts, more preferably less thanabout 50 microwatts, and most preferably less than about 25 microwatts.

In one alternative embodiment, the continuous glucose sensor comprises atranscutaneous sensor such as described in U.S. Pat. No. 6,565,509 toSay et al. In another alternative embodiment, the continuous glucosesensor comprises a subcutaneous sensor such as described with referenceto U.S. Pat. No. 6,579,690 to Bonnecaze et al. and U.S. Pat. No.6,484,046 to Say et al. In another alternative embodiment, thecontinuous glucose sensor comprises a refillable subcutaneous sensorsuch as described with reference to U.S. Pat. No. 6,512,939 to Colvin etal. In another alternative embodiment, the continuous glucose sensorcomprises an intravascular sensor such as described with reference toU.S. Pat. No. 6,477,395 to Schulman et al. In another alternativeembodiment, the continuous glucose sensor comprises an intravascularsensor such as described with reference to U.S. Pat. No. 6,424,847 toMastrototaro et al. All of the above patents are incorporated in theirentirety herein by reference. In general, it should be understood thatthe disclosed embodiments are applicable to a variety of continuousglucose sensor configurations.

Receiver

The preferred embodiments provide an integrated system, which includes areceiver 14 that receives and processes the raw data stream from thecontinuous glucose sensor 12. The receiver can perform all or some ofthe following operations: a calibration, converting sensor data,updating the calibration, evaluating received reference and sensor data,evaluating the calibration for the analyte sensor, validating receivedreference and sensor data, displaying a meaningful glucose value to auser, calculating therapy recommendations, validating recommendedtherapy, adaptive programming for learning individual metabolicpatterns, and prediction of glucose values, for example. Somecomplementary systems and methods associated with the receiver aredescribed in more detail with reference to U.S. Patent Publication No.US-2005-0027463-A1 which is incorporated herein by reference in itsentirety. FIGS. 9 to 11 describe some processes that can be programmedinto the receiver. Additionally, the receiver 14 of the preferredembodiments works together with the other components of the system (forexample, the medicament delivery device 16 and the single point glucosemonitor 18) to provide enhanced functionality, convenience, and safety,such as described in more detail herein. FIGS. 4 to 7 are illustrates ofa few exemplary integrated systems of the preferred embodiments, each ofwhich include the receiver, such as described in more detail herein.

In some embodiments, the receiver 14 is a PDA- or pager-sized housing46, for example, and comprises a user interface 48 that has a pluralityof buttons 50 and a liquid crystal display (LCD) screen, which caninclude a backlight. In some embodiments, the receiver can take otherforms, for example a computer, server, or other such device capable ofreceiving and processing the data such as described herein. In someembodiments the user interface can also include a keyboard, a speaker,and a vibrator such as described with reference to FIG. 8. The receiver46 comprises systems (for example, electronics) necessary to receive,process, and display sensor data from the glucose sensor 12, such asdescribed in more detail with reference to FIG. 8. The receiver 14processes data from the continuous glucose sensor 12 and additionallyprocesses data associated with at least one of the medicament deliverydevice 16, single point glucose meter 16, and user 8.

In some embodiments, the receiver 14 is integrally formed with at leastone of the medicament delivery device 16, and single point glucosemonitor 18. In some embodiments, the receiver 14, medicament deliverydevice 16 and/or single point glucose monitor 18 are detachablyconnected, so that one or more of the components can be individuallydetached and attached at the user's convenience. In some embodiments,the receiver 14, medicament delivery device 16, and/or single pointglucose monitor 18 are separate from, detachably connectable to, orintegral with each other; and one or more of the components are operablyconnected through a wired or wireless connection, allowing data transferand thus integration between the components. In some embodiments, one ormore of the components are operably linked as described above, whileanother one or more components (for example, the syringe or patch) areprovided as a physical part of the system for convenience to the userand as a reminder to enter data for manual integration of the componentwith the system. Some exemplary embodiments are described with referenceto FIGS. 4 to 7, however suffice it to say that each of the componentsof the integrated system can be manually, semi-automatically, orautomatically integrated with each other, and each component can be inphysical and/or data communication with another component, which caninclude wireless connection, wired connection (for example, via cablesor electrical contacts), or the like. In some embodiments, the receiveris configured to process data from the glucose sensor, an auxiliarysensor and/or the medicament delivery device, and can include acontroller module.

Medicament Delivery Device

The preferred embodiments provide an integrated system 10, whichincludes a medicament delivery device 16 for administering a medicamentto the host 8. The integrated medicament delivery device can be designedfor bolus injection/infusion, basal injection/infusion, continuousinjection/infusion, inhalation, transdermal absorption, other method foradministering medicament, or any combinations thereof. In one exemplaryembodiment, the medicament delivery device is an infusion pumpconfigured for transcutaneous (e.g., injection/infusion and absorptioninto the subcutaneous tissue), intraperitoneal or intravenous infusion.In some embodiments, the infusion device is wholly implantable. In otherembodiments, the infusion device is worn outside of the body, withinfusion via a catheter. In some embodiments, the infusion device isconfigured for one or more maintenance functions, such as but notlimited to checking for catheter clogs or monitoring the rate of insulinleaving the infusion device or the remaining volume of insulin withinthe pump. In some embodiments, the medicament delivery device is aninsulin pump configured to deliver insulin to the host. In someembodiments, the insulin pump is further configured to receive andprocess instructions for delivery of an insulin therapy from acontroller module.

In some embodiments, the medicament delivery device is an injection penconfigured to inject insulin transcutaneously. In some embodiments, themedicament delivery device is an inhaler that delivers an inhalableinsulin formulation. In other embodiments, the medicament deliverydevice is an oral medicament, such as an insulin preparation formulatedfor buccal absorption. In still other embodiments, the medicamentdelivery device is configured for transdermal delivery, such as atransdermal patch. In some embodiments, the at least two insulindelivery devices are used in conjunction with each other. For example,delivery of insulin by an infusion device (e.g., a pump) can besupplemented with delivery of another medicament (e.g., either the sameor different types of insulin, or another medicament such as glucagon)with a second medicament delivery device, such as but not limited to apen, a transdermal patch or an inhaler. For example, in somecircumstances, a host can use an infusion pump to deliver rapid actinginsulin and a patch to constantly deliver a slow-acting insulin. Inanother exemplary circumstance, a transcutaneous insulin pump canprovide the insulin therapy, which can be supplemented by instructionsto provide a therapeutic dose of glucagon via an inhaler or an oralpreparation. The term medicament includes any substance used in therapyfor a host using the system 10, for example, insulin, glucagon, orderivatives thereof. PCT International Publication No. WO02/43566-A1describes glucose, glucagon, and vitamins A, C, or D that can be usedwith the preferred embodiments. U.S. Pat. No. 6,051,551 and U.S. Pat.No. 6,024,090 describe types of insulin suitable for inhalation that canbe used with the preferred embodiments. U.S. Pat. No. 5,234,906, U.S.Pat. No. 6,319,893, and European Patent No. EP-760677-B1 describevarious derivatives of glucagon that can be used with the preferredembodiments. U.S. Pat. No. 6,653,332 describes a combination therapythat can be used with the preferred embodiments. U.S. Pat. No. 6,471,689and PCT International Publication No. WO81/01794-A1 describe insulinuseful for delivery pumps that can be used with the preferredembodiments. U.S. Pat. No. 5,226,895 describes a method of providingmore than one type of insulin that can be used with the preferredembodiments. Each of the above references is incorporated herein byreference in its entirety and the medicaments and methods disclosed canbe useful in the preferred embodiments.

As described elsewhere herein, in preferred embodiments, the system isconfigured to substantially mimic the body's metabolic response tochanges in glucose (e.g., the host's blood sugar concentration), similarto the response of a pancreatic β-cell to changes in glucoseconcentration. As is understood by one skilled in the art, insulinactivity can be influenced by a variety of factors, such as but notlimited to method/location of delivery (e.g., injected transcutaneously,infused IV or intraperitoneally, inhaled, etc.), the host's insulinsensitivity, method of insulin preparation, and the like. However, it ispossible to compare different insulins by comparing their time-activityprofiles (TAP), as defined by methods of Frohnauer, et al. 2001, in“Graphical Human Insulin Time-Activity Profiles Using StandardizedDefinitions,” Diab. Tech. & Therap. 3(3):419-429. Table 1 presents theTAPs of some purified human insulins (e.g., wild type and/or analogs)and one exemplary flash insulin (described elsewhere herein).

TABLE 1 Insulin Formulation Onset (hrs) T_(i50) (hrs) Peak (hrs) T_(d50)(hrs) Duration (hrs) Humulin R Plasma Insulin Level 0.08-1.0  0.5-3.25 4.0-12.0 Glucose Infusion Rate 0.25-1.0 0.6-1.25 1.5-4.0 4.0-7.0  9.5-12.0 NPH Plasma Insulin Level 0.08-1.5 1.0-8.0  6.0-28.0 GlucoseInfusion Rate 0.25-2.0 1.25-3.25   3.5-10.0 8.5-18.0 14.0-27.0 LentePlasma Insulin Level  0.5-2.25 4.0-6.5 21.0-24.0 Glucose Infusion Rate0.75-2.0 3.0-4.5   9.4-12.0 19.25-23.5  21.0-24.0 Ultralente PlasmaInsulin Level  0.5-3.0  4.0-16.0  9.0-28.0 Glucose Infusion Rate0.75-3.0 3.5-8.0   5.0-14.5 17.0-22.0  22.5-36.6 Insulin lispro PlasmaInsulin Level  0.08-0.25 0.6-1.0 3.0-8.0 Glucose Infusion Rate 0.16-0.50.6-0.75 1.25-2.0  2.5-4.25 5.0-7.0 Flash Insulin Plasma Insulin Level ≦0.08-≦0.25 ≦0.6-≦1.0 ≦3.0-≦8.0 Glucose Infusion Rate ≦0.25-≦0.5≦0.6-≦0.75 ≦1.25-≦2.0  ≦2.5-≦4.25 ≦5.0-≦7.0 Humulin R = a purified wildtype human insulin; NPH = a purified human insulin analog (Humulin N)Lente = another purified human insulin analog (Humulin L) Ultralente =yet another purified human insulin analog (Humulin U) T_(i50) = the timepoint at which insulin activity is half of the maximal activity, as thelevel increases. T_(d50) = the time point at which the insulin activityis half of the maximal activity, as the level decreases.

FIG. 4 illustrates the TAP of Humulin R (according to Frohnauer, et al.2001, in “Graphical Human Insulin Time-Activity Profiles UsingStandardized Definitions,” Diab. Tech. & Therap. 3(3):419-429) and threepossible TAPs for a “Flash Insulin,” which is described below. As isknown to those skilled in the art, the times of onset, peak and durationof an insulin's activity can be determined by conducting glucose clampstudies (e.g., on human volunteers) and examining the pharmacokineticsof the insulin (e.g., by examining the plasma insulin level or theglucose infusion rate during glucose clamp studies). According to themethods of Frohnauer, et al., “onset” of an insulin's activity can bedetermined by graphing the insulin's activity over an extended period oftime (e.g., about 24- to 38-hours). On a graph of an insulin's activity(see FIG. 4), onset occurs at a time point between last baselinemeasurement and the first measurement above the baseline. In somecircumstances, onset of an insulin's activity can be very abrupt orsharp, occurring within a few minutes. In other circumstances, onset canbe prolonged, taking up to several hours. The peak of insulin activityoccurs at a time point between the first maximum activity measurementand the last maximum activity measurement. In some circumstances, thepeak of activity is very brief, such as a single time point. In othercircumstances, the peak is prolonged (e.g., lasts a period of minutes orhours) and falls within a range of consecutive time points. The durationof an insulin's activity is the length of time during which the insulinhas been active (e.g., functioning, working in the body), up to thetermination of activity. At termination, the insulin's activitygenerally declines, tapers off and/or plateau's out (e.g., flattensout). On a graph of the insulin's activity, activity termination occursbetween the last point above horizontal and the first point on thehorizontal. In some circumstances, an insulin's termination can beabrupt, such as at a single point. In other circumstances, an insulin'stermination can be extended over a period of several minutes or a fewhours.

In some embodiments, the insulin used in conjunction with the integratedsystem 10 is configured such that the system mimics the function of apancreatic β-cell, with a substantially immediate onset of activity, avery rapid peak and a very brief duration (as determined by plasmainsulin concentration according to the methods of Frohnauer et al). Insome embodiments, the insulin is configured to have an onset time ofabout 5-minutes to about 10-minutes or less and a peak of activity ofabout 5-minutes to about 1.25-hours. Additionally, the insulin isconfigured to have a substantially short (e.g., brief) duration of about3-hours or less.

In some embodiments, a very rapid-acting insulin is preferred, such thatthe insulin can be delivered by a system having an on/off controller, asdescribed elsewhere herein. Such an insulin is referred to herein as a“Flash Insulin.” In FIG. 4, three possible TAPs, of an exemplary flashinsulin, are denoted by the curves labeled FI-1, FI-2 and FI-3.Depending upon the flash insulin developed, other TAPs are possible. Inpreferred embodiments, a flash insulin is configured to have asubstantially “instant on” onset, such that the flash insulin reachesits peak of activity within a short time after delivery. For example, insome embodiments, a flash insulin's onset can occur within about10-minutes or less (e.g., after delivery), preferably within about6-minutes or less. In another example, in some embodiments, the flashinsulin's peak of activity can occur within about 2-minutes to about30-minutes, preferably within about 5-minutes to about 15-minutes. Inanother example, in some embodiments, the flash insulin's duration issubstantially short, such as less than about 3, 2 or 1-hours. In somepreferred embodiments, the flash insulin's activity peaks within about4, 5, 8, 10, 15 or 20-minutes of the insulin's onset of activity and/orinfusion of the insulin into the host. In some more preferredembodiments, the flash insulin's duration is sufficiently brief that“dose stacking” (e.g., from sequential doses) has substantially noeffect on the host's glucose concentration. For example, in someembodiments, the flash insulin's duration is about 10, 20, 30 or40-minutes, preferably less than about 20-minutes. In some embodiments,the flash insulin is configured for use with an on/off controller(discussed elsewhere herein), such that when the on instruction isselected, the flash insulin is delivered at substantially constant rate.

Manual Integration

In some embodiments, the medicament delivery device 16 is a manualdelivery device, for example a syringe, inhaler, transdermal patch, celltransplantation device, and/or manual pump for manual integration withthe receiver. Manual integration includes medicament delivery deviceswherein a user (for example, host or doctor) manually selects theamount, type, and/or time of delivery. In some embodiments, themedicament delivery device 16 is any syringe suitable for injecting amedicament, as is appreciated by one skilled in the art. One example ofa syringe suitable for the medicament delivery device of the preferredembodiments is described in U.S. Pat. No. 5,137,511, which isincorporated herein by reference in its entirety.

FIGS. 5A and 5B are perspective views of an integrated system 10 in oneembodiment, wherein a receiver 14 is integrated with a medicamentdelivery device 16 in the form of a manual syringe 54, and optionallyincludes a single point glucose monitor 18, which will be described inmore detail elsewhere herein. The receiver 14 receives, processes, anddisplays data from the continuous glucose monitor 12, such as describedin more detail above, and can also receive, process, and display datamanually entered by the user. In some embodiments, the receiver includesalgorithms that use parameters provided by the continuous glucosesensor, such as glucose concentration, rate-of-change of the glucoseconcentration, and acceleration of the glucose concentration to moreparticularly determine the type, amount, and time of medicamentadministration. The medicament delivery device 16 is in the form of asyringe 54, which can comprise any known syringe configuration, such asdescribed in more detail above. In some embodiments, the syringe 54includes a housing, which is designed to hold a syringe as well as aplurality of types and amounts of medicament, for example fast-actinginsulin, slow-acting insulin, and glucagon. In some embodiments, thesyringe is detachably connectable to the receiver 14, and the receiver14 provides and receives information to and from the host associatedwith the time, type, and amount of medicament administered. In someembodiments, the syringe is stored in a holder that is integral with ordetachably connected to the receiver 14. In some embodiments, thesyringe 54 can be detachable connected directly to the receiver,provided in a kit with the receiver, or other configuration, whichprovides easy association between the syringe and the receiver.

Referring now to the integration between the syringe and the receiver,it is noted that the receiver can be programmed with information aboutthe time, amount, and types of medicament that can be administered withthe syringe, for example. In some embodiments during set-up of thesystem, the host and/or doctor manually enters information about theamounts and types of medicament available via the syringe of theintegrated system. In some alternative embodiments,manufacturer-provided data can be downloaded to the receiver so that thehost and/or doctor can select appropriate information from menus on thescreen, for example, to provide easy and accurate data entry. Thus, byknowing the available medicaments, the receiver can be programmed tocustomize the host's therapy recommendations considering available typesand amounts of medicaments in combination with concentration,rate-of-change, and/or acceleration of the host's glucose. While notwishing to be bound by theory, it is believed that by storing availablemedicament therapies, the receiver is able to customize medicamentcalculations and recommend appropriate therapy based glucose on trendinformation and the preferred types and the amounts of medicamentavailable to the host.

Subsequently in some embodiments, once the host has administered amedicament (including via the syringe and or by other means), theamount, type, and/or time of medicament administration are input intothe receiver by the host. Similarly, the receiver can be programmed withstandard medicaments and dosages for easy selection by the host (forexample, menus on the user interface). This information can be used bythe receiver to increase the intelligence of the algorithms used indetermining the glucose trends and patterns that can be useful inpredicting and analyzing present, past, and future glucose trends, andin providing therapy recommendations, which will be described in moredetail below. Additionally, by continuously monitoring the glucoseconcentration over time, the receiver provides valuable informationabout how a host responds to a particular medicament, which informationcan be used by a doctor, host, or by the algorithms within the receiver,to determine patterns and provide more personalized therapyrecommendations. In other words, in some embodiments, the receiverincludes programming that learns the patterns (for example, anindividual's metabolic response to certain medicament deliveries andhost behavior) and to determine an optimum time, amount, and type ofmedicament to delivery in a variety of conditions (e.g., glucoseconcentration, rate-of-change, and acceleration). While not wishing tobe bound by theory, it is believed that by continuously monitoring anindividual's response to various medicaments, the host's glucose levelscan be more proactively treated, keeping the diabetic host within safeglucose ranges substantially all the time.

In some embodiments, the receiver includes programming to predictglucose trends, such as described in U.S. Patent Publication No.US-2005-0203360-A1, which is incorporated herein by reference in itsentirety. In some embodiments, the predictive algorithms consider theamount, type, and time of medicament delivery in predicting glucosevalues. For example, a predictive algorithm that predicts a glucosevalue or trend for the upcoming 15 to 20 minutes uses a mathematicalalgorithm (for example, regression, smoothing, or the like) such asdescribed in the above-cited U.S. Patent Publication No.US-2005-0203360-A1 to project a glucose value. However outsideinfluences, including medicament delivery can cause this projection tobe inaccurate. Therefore, some embodiments provide programming in thereceiver that uses the medicament delivery information received from thedelivery device 14, in addition to other mathematical equations, to moreaccurately predict glucose values in the future.

In some alternative embodiments, the medicament delivery device 16includes one or more transdermal patches 58 suitable for administeringmedicaments as is appreciated by one skilled in the art. PCTInternational Publication No. WO02/43566 describes one such transdermalpatch, which can be used in the preferred embodiments. Although theabove-cited reference and description associated with the FIGS. 6A to 6Cdescribe a medicament (for example, glucagon) useful for treatinghypoglycemia, it is understood that transdermal patches that release amedicament (for example, insulin) useful for treating hyperglycemia arealso contemplated within the scope of the preferred embodiments.

FIGS. 6A to 6C are perspective views of an integrated system 10 in oneembodiment, wherein a receiver 14 is integrated with a medicamentdelivery device 16 in the form of one or more transdermal patches 58housed within a holder 56, and optionally includes a single pointglucose monitor 18, which will be described in more detail elsewhereherein. The receiver 14 receives, processes, and displays data from thecontinuous glucose monitor 12, such as described in more detail above.The medicament delivery device 16 is in the form of one or moretransdermal patches 58 held in a holder 56, which can comprise any knownpatch configuration.

The integration of the patches 58 with the receiver 14 includes similarfunctionality and provides similar advantages as described withreference to other manual integrations including manual medicamentdelivery devices (for example, syringe and inhaler). However, a uniqueadvantage can be seen in the integration of a continuous glucose sensorwith a glucagon-type patch. Namely, a continuous glucose sensor, such asdescribed in the preferred embodiments, provides more than single pointglucose readings. In fact, because the continuous glucose sensor 12knows the concentration, rate-of-change, acceleration, the amount ofinsulin administered (in some embodiments), and/or individual patternsassociated with a host's glucose trends (learned over time as describedin more detail elsewhere herein), the use of the glucagon patch can beiteratively optimized (inputting its usage into the receiver andmonitoring the individual's metabolic response) to proactively preempthypoglycemic events and maintain a more controlled range of glucosevalues. This can be particularly advantageous for nighttime hypoglycemiaby enabling the diabetic host (and his/her caretakers) to improveoverall nighttime diabetic health. While not wishing to be bound bytheory, the integration of the continuous glucose sensor and transdermalglucagon-type patch can provide diabetic hosts with a long-term solutionto reduce or avoid hypoglycemic events.

In some embodiments, the holder 58 is detachably connectable to thereceiver 14 (for example on the side opposite the LCD), which enablesconvenient availability of the patch to the host when the receiverindicates that a medicament (for example, glucose or glucagon) isrecommended. It is further noted that although this holder is shownwithout another medicament delivery device 16 in the illustrations ofFIGS. 6A to 6C, other medicaments (for example, insulin pen, insulinpump, such as described with reference to FIGS. 7 and 8) can beintegrated into the system in combination with the medicament patchillustrated herein. While not wishing to be bound by theory, it isbelieved that by combining medicaments that aid the diabetic host indifferent ways (for example, medicaments for treating hyper- andhypo-glycemic events, or, fast-acting and slow-acting medicaments), asimplified comprehensive solution for treating diabetes can be provided.

Manual integration of delivery devices with the continuous glucosesensor 12 of the preferred embodiments can additionally be advantageousbecause the continuous device of the preferred embodiments is able totrack glucose levels long-term (for example weeks to months) andadaptively improve therapy decisions based on the host's response overtime.

In some alternative embodiments, the medicament delivery device 16includes an inhaler or spray device suitable for administering amedicament into the circulatory system, as is appreciated by one skilledin the art. Some examples of inhalers suitable for use with thepreferred embodiments include U.S. Pat. No. 6,167,880, U.S. Pat. No.6,051,551, and U.S. Pat. No. 6,024,090, which are incorporated herein byreference in their entirety. In some embodiments, the inhaler or spraydevice is considered a manual medicament delivery device, such asdescribed with reference to FIGS. 5 and 6, wherein the inhaler or sprayis manually administered by a host, and wherein the host manually entersdata into the continuous receiver about the time, amount, and types oftherapy. However, it is also possible that the inhaler or spray deviceused for administering the medicament can also comprise a processormodule and operable connection to the receiver (for example, RF), suchthat data is sent and received between the receiver and inhaler or spraydevice, making it a semi-automated integration, which is described inmore detail with reference to the integrated insulin pen below, forexample.

In some embodiments, the inhaler or spray device is integrally housedwithin, detachably connected to, or otherwise physically associated with(for example, in a kit) to the receiver. The functionality andadvantages of the integrated inhaler or spray device are similar tothose described with reference to the syringe and/or patch integration,above. It is noted that the inhaler or spray device can be provided incombination with any other of the medicament delivery devices of thepreferred embodiments, for example, a fast-acting insulin inhaler and aslow acting insulin pump can be advantageously integrated into thesystem of the preferred embodiments and utilized at the appropriate timeas is appreciated by one skilled in the art. In some embodiments,wherein the inhaler or spray device includes a semi-automatedintegration with the receiver, the inhaler or spray device can byphysically integrated with receiver such as described above and alsooperably connected to the receiver, for example via a wired (forexample, via electrical contacts) or wireless (for example, via RF)connection.

In one alternative embodiment, a manual medicament delivery pump isimplanted such as described in U.S. Pat. No. 6,283,944, which isincorporated herein by reference in its entirety. In this alternativeembodiment, the host-controlled implantable pump allows the host topress on the device (through the skin) to administer a bolus injectionof a medicament when needed. It is believed that providing glucagon orother medicament for treating hypoglycemia within this device willprovide the ease and convenience that can be easily released by the hostand/or his or her caretaker when the continuous glucose sensor indicatessevere hypoglycemia, for example. In some alternative embodiments, themanual implantable pump is filled with insulin, or other medicament fortreating hyperglycemia. In either case, the manual pump and continuousglucose sensor will benefit from manual integrations described in moredetail above.

In another alternative embodiment, a cell transplantation device, suchas described in U.S. Pat. No. 6,015,572, U.S. Pat. No. 5,964,745, andU.S. Pat. No. 6,083,523, which are incorporated herein by reference intheir entirety, is manually integrated with the continuous sensor of thepreferred embodiments. In this alternative embodiment, a host would beimplanted with beta islet cells, which provide insulin secretionresponsive to glucose levels in the body. The receiver associated withthe implantable glucose sensor can be programmed with information aboutthe cell transplantation (for example, time, amount, type, etc). In thisway, the long-term continuous glucose sensor can be used to monitor thebody's response to the beta islet cells. This can be particularlyadvantageous when a host has been using the continuous glucose sensorfor some amount of time prior to the cell transplantation, and thechange in the individual's metabolic patterns associated with thetransplantation of the cells can be monitored and quantified. Because ofthe long-term continuous nature of the glucose sensor of the preferredembodiments, the long-term continuous effects of the celltransplantation can be consistently and reliably monitored. Thisintegration can be advantageous to monitor any person's response to celltransplantation before and/or after the implantation of the cells, whichcan be helpful in providing data to justify the implantation of isletcells in the treatment of diabetes.

It is noted that any of the manual medicament delivery devices can beprovided with an RF ID tag or other communication-type device, whichallows semi-automated integration with that manual delivery device, suchas described in more detail below.

Semi-Automated Integration

semi-automated integration of medicament delivery devices 16 in thepreferred embodiments includes any integration wherein an operableconnection between the integrated components aids the user (for example,host or doctor) in selecting, inputting, or calculating the amount,type, or time of medicament delivery of glucose values, for example, bytransmitting data to another component and thereby reducing the amountof user input required. In the preferred embodiments, semi-automated canalso refer to a fully automated device (for example, one that does notrequire user interaction), wherein the fully automated device requires avalidation or other user interaction, for example to validate or confirmmedicament delivery amounts. In some embodiments, the semi-automatedmedicament delivery device is an inhaler or spray device, a pen orjet-type injector, or a transdermal or implantable pump.

FIGS. 7A and 7B are perspective views of an integrated system 10 in oneembodiment, wherein a receiver 14 is integrated with a medicamentdelivery device 16 in the form of a pen or jet-type injector,hereinafter referred to as a pen 60, and optionally includes a singlepoint glucose monitor 18, which will be described in more detailelsewhere herein. The receiver 14 receives, processes, and displays datafrom the continuous glucose monitor 12, such as described in more detailabove. The medicament delivery pen 60 of the preferred embodimentsincludes any pen-type injector, such as is appreciated by one skilled inthe art. A few examples of medicament pens that can be used with thepreferred embodiments, include U.S. Pat. No. 5,226,895, U.S. Pat. No.4,865,591, U.S. Pat. No. 6,192,891, and U.S. Pat. No. 5,536,249, each ofwhich are incorporated herein by reference in its entirety.

FIG. 7A is a perspective view of an integrated system 10 in embodiment.The integrated system 10 is shown in an attached state, wherein thevarious elements are held by a mechanical means, as is appreciated byone skilled in the art. The components 14, 16, and 18 (optional) arealso in operable connection with each other, which can include a wiredor wireless connection. In some embodiments, the components includeelectrical contacts that operably connect the components together whenin the attached state. In some embodiments, the components are operablyconnected via wireless connection (for example, RF), and wherein thecomponents may or may not be detachably connectable to each other. FIG.7B shows the components in an unattached state, which can be useful whenthe host would like to carry minimal components and/or when thecomponents are integrated via a wireless connection, for example.

Medicament delivery pen 60 includes at least a processor module and awired or wireless connection to the receiver 14, which are described inmore detail with reference to FIG. 9. In some embodiments, the pen 60includes programming that receives instructions sent from the receiver14 regarding type and amount of medicament to administer. In someembodiments, wherein the pen includes more than one type of medicament,the receiver provides the necessary instructions to determine which typeor types of medicament to administer, and can provide instructionsnecessary for mixing the one or more medicaments. In some embodiments,the receiver provides the glucose trend information (for example,concentration, rate-of-change, acceleration, or other user inputinformation) and pen 60 includes programming necessary to determineappropriate medicament delivery.

Subsequently, the pen 60 includes programming to send informationregarding the amount, type, and time of medicament delivery to thereceiver 14 for processing. The receiver 14 can use this informationreceived from the pen 60, in combination with the continuous glucosedata obtained from the sensor, to monitor and determine the host'sglucose patterns to measure their response to each medicament delivery.Knowing the host's individual response to each type and amount ofmedicament delivery can be useful in adjusting or optimizing the host'stherapy. It is noted that individual metabolic profiles (for example,insulin sensitivity) are variable from host to host. While not wishingto be bound by theory, it is believed that once the receiver has learned(for example, monitored and determined) the individual's metabolicpatterns, including glucose trends and associated medicament deliveries,the receiver can be programmed to adjust and optimize the therapyrecommendations for the host's individual physiology to maintain theirglucose levels within a desired target range. In alternativeembodiments, the pen 60 can be manually integrated with the receiver.

In some embodiments, the receiver includes algorithms that useparameters (e.g., data) provided by the continuous glucose sensor, suchas glucose concentration, rate-of-change of the glucose concentration,and acceleration of the glucose concentration to more particularlydetermine the type, amount, and time of medicament administration. Infact, all of the functionality of the above-described manual andsemi-automated integrated systems, including therapy recommendations,adaptive programming for learning individual metabolic patterns, andprediction of glucose values, can be applied to the semi-automatedintegrated system 10, such as described herein. However, thesemi-automated integrated sensing and delivery system additionallyprovides convenience by automation (for example, data transfer throughoperable connection) and reduced opportunity for human error than can beexperienced with the manual integration.

In some alternative embodiments, the semi-automated integration providesprogramming that requires at least one of the receiver 14, single pointglucose monitor 18, and medicament delivery device 16 to be validated orconfirmed by another of the components to provide a fail safe accuracycheck; in these embodiments, the validation includes algorithmsprogrammed into any one or more of the components. In some alternativeembodiments, the semi-automated integration provides programming thatrequires at least one of the receiver 14 and medicament delivery device16 to be validated or confirmed by an a human (for example, confirm theamount and/or type of medicament). In these embodiments, validationprovides a means by which the receiver can be used adjunctively, whenthe host or doctor would like to have more control over the host'stherapy decisions, for example. See FIGS. 10 to 12 for processes thatcan be implemented herein.

Although the above description of semi-automated medicament delivery ismostly directed to an integrated delivery pen, the same or similarintegration can be accomplished between a semi-automated inhaler orspray device, and/or a semi-automated transdermal or implantable pumpdevice. Additionally, any combination of the above semi-automatedmedicament delivery devices can be combined with other manual and/orautomated medicament delivery device within the scope of the preferredembodiments as is appreciated by one skilled in the art.

In some embodiments, the semi-automated integrated system 10 includes adynamic bolus controller module that is configured to intelligentlyevaluate an engaged (e.g., selectable) bolus constraint (e.g., pre-setand/or programmable) and internally derived data, and to calculate aninsulin therapy (e.g., dose) less than or equal to the maximum totalinsulin dose associated with the engaged bolus constraint, in responseto the host engaging the bolus constraint, such as described in moredetail elsewhere herein. Preferably, the determination of the insulintherapy is based solely on the internally derived data and the engagedbolus constraint. In some preferred embodiments, the evaluation and/orcalculation of therapy are performed iteratively. In some embodiments, abolus constraint can be engaged (e.g., selected, initiated, activated)by pressing a programmable button or key, actuating a switch, selectingfrom a menu (e.g., scroll, pop-up or tab) and the like. In someembodiments, the system includes two or more bolus constraints, such asconstraints associated with different types of meals and/or withdifferent events. For example, one or more bolus constraint buttons canbe programmed by the user (e.g., the host or a caretaker of the host)for insulin therapies sufficient to cover an average breakfast, lunch ordinner, to cover a high carbohydrate or high fat meal, or as acorrective insulin dose and the like. In a further embodiment, thesystem is configured to request host validation of the calculated bolusinsulin therapy (e.g., by selecting yes or no, OK).

In some embodiments, the system is configured to include an on/offcontroller module and/or a dynamic basal controller module. On/off anddynamic basal controller modules are discussed in detail elsewhereherein.

Automated Integration

Automated integration medicament delivery devices 16 in the preferredembodiments are any delivery devices wherein an operable connectionbetween the integrated components provides for full control of thesystem without required user interaction. Transdermal and implantablepumps are examples of medicament delivery devices that can be used withthe preferred embodiments of the integrated system 10 to provideautomated control of the medicament delivery device 16 and continuousglucose sensor 12. Some examples of medicament pumps that can be usedwith the preferred embodiments include, U.S. Pat. No. 6,471,689, PCTInternational Publication No. WO81/01794, and European Patent No.EP-1281351-B, each of which is incorporated herein by reference in itsentirety.

FIGS. 8A to 8C are perspective views of an integrated system in oneembodiment, wherein a sensor and delivery pump, which are implanted ortransdermally inserted into the host, are operably connected to anintegrated receiver, and optionally include a single point glucosemonitor. FIG. 8A is a perspective view of a host 8, in which isimplanted or transdermally inserted a sensor 12 and a pump 70. FIGS. 8Band 8C are perspective views of the integrated receiver and optionalsingle point glucose monitor in attached and unattached states. The pump70 can be of any configuration known in the art, for example, such ascited above.

The receiver 14 receives, processes, and displays data associated withthe continuous glucose monitor 12, data associated with the pump 70, anddata manually entered by the host 8. In some embodiments, the receiverincludes algorithms that use parameters provided by the continuousglucose sensor, such as glucose concentration, rate-of-change of theglucose concentration, and acceleration of the glucose concentration todetermine the type, amount, and time of medicament administration. Infact, all of the functionality of the above-described manual andsemi-automated integrated systems, including therapy recommendations,confirmation or validation of medicament delivery, adaptive programmingfor learning individual metabolic patterns, and prediction of glucosevalues, can be applied to the fully automated integrated system 10, suchas described herein with reference to FIGS. 8A to 8C. However, the fullyautomated sensing and delivery system can run with or without userinteraction. U.S. Patent Publication No. US-2003-0028089-A1 providessome systems and methods for providing control of insulin, which can beused with the preferred embodiments, and is incorporated herein byreference in its entirety.

In some embodiments of the automated integrated system 10, a fail-safemode is provided, wherein the system is programmed with conditionswhereby when anomalies or potentially clinically risky situations arise,for example when a reference glucose value (for example, from an SMBG)indicates a discrepancy from the continuous sensor that could cause riskto the host if incorrect therapy is administered. Another example of asituation that may benefit from a validation includes when a glucosevalues are showing a trend in a first direction that shows a possibilityof “turn around,” namely, the host may be able to reverse the trend witha particular behavior within a few minutes to an hour, for example. Insuch situations, the automated system can be programmed to revert to asemi-automated system requiring user validation or other userinteraction to validate the therapy in view of the situation.

It is noted that in the illustrated embodiment, only one receiver 14 isshown, which houses the electronics for both the medicament deliverypump 70 and the continuous sensor 12. Although it is possible to housethe electronics in two different receiver housings, providing oneintegrated housing 14 increases host convenience and minimizes confusionor errors. In some embodiments, the sensor receiver electronics and pumpelectronics are separate, but integrated. In some alternativeembodiments, the sensor and pump share the same electronics.

Additionally, the integrated receiver for the sensor and pump, can befurther integrated with any combination with the above-describedintegrated medicament delivery devices, including syringe, patch,inhaler, and pen, as is appreciated by one skilled in the art.

In some embodiments, the fully automated integrated system 10 includesan on/off controller module, as described elsewhere herein. Preferably,the on/off controller module is configured to intelligently andadaptively evaluate only internally derived data relative to apre-programmed glucose boundary (e.g., about 70, 80, 90, 100, 110, 120,130, 140, 150, or 160 mg/dl glucose) and to select between on and offinstructions that actuate the system's integrated insulin deliverydevice. In one embodiment, integrated system 10 is configured toautomatically (e.g., iteratively, continually or continuously) monitorand manage the host's glucose level in real-time, similarly to theglucose regulation by the pancreatic β-cells of a non-diabetic person.In generally, the glucose boundary is selected based on when insulin is,or is not, to be delivered to the host.

In some embodiments, the automated system includes an on/off controllerand is configured for use with a flash insulin (e.g., an insulin havinga substantially “instant on,” rapid peak and short duration TAP, asdescribed in the section entitled “Medicament Delivery Device”), suchthat the on/off controller can iteratively (e.g., automatically,periodically, or continually) evaluate the internally derived data,calculate and deliver flash insulin doses over a period of time (e.g.,minutes, hours, days, etc.) and the effect of insulin dose stacking(e.g., to the host) is substantially negligible and/or can bealgorithmically accounted for. On/off controller modules are describedin greater detail in the section entitled “On/off Controller Module,”and, for example, with reference to FIG. 15.

In some embodiments, the automated integrated system 10 includes adynamic basal controller module configured to intelligently andadaptively evaluate solely internally derived data relative to a basalprofile, and to calculate an insulin therapy within the basal profile,such that the host's glucose is substantially maintained within a targetrange over a period of hours, days or weeks, with the exception ofexpected increases in glucose associated with meals and the like. Ingeneral, the target range is a range of euglycemic glucoseconcentrations. Two exemplary target ranges are glucose concentrationsfrom about 80 mg/dl to about 140 mg/dl and from about 100-mg-dl to about160 mg/dl. Dynamic basal controller modules are described in greaterdetail in the section entitled “Dynamic Basal Controller Module,” and,for example, with reference to FIG. 16.

In some embodiments, the fully automated integrated system is configuredto continuously (e.g., intermittently, iteratively, periodically, orautomatically) adaptively monitor and evaluate the host's metabolicprofile and to determine (e.g., calculate) an insulin therapy. As isknown to one skilled in the art, the host's metabolic profile canfluctuate over a period of days or weeks, depending upon the host'sactivity level and state of health, the types of foods the host isconsuming, medications, and the like. Preferably, the controller module(e.g., on/off, basal and/or bolus controller modules) is configured toadaptively and intelligently adjust one or more system parameters (e.g.,glucose boundary, basal profile, bolus constraint, insulin deliveryrate, and the like) in response to internally derived data and thehost's metabolic profile. While not wishing to be bound by theory, it isbelieved that configuring the fully automated integrated system toadaptively monitor and evaluate the user's metabolic profile promotesoptimal insulin dosing, improves system accuracy and reduces the numberof host hypoglycemic episodes, which ultimately promotes improved hosthealth and safety.

Single Point Glucose Monitor

In the illustrated embodiments (FIGS. 5 to 8), the single point glucosemonitor includes a meter for measuring glucose within a biologicalsample including a sensing region that has a sensing membraneimpregnated with an enzyme, similar to the sensing membrane describedwith reference to U.S. Pat. No. 4,994,167 and U.S. Pat. No. 4,757,022,each which is incorporated herein in its entirety by reference. However,in alternative embodiments, the single point glucose monitor can useother measurement techniques such as conventional finger stick/teststrip meters, optical devices, and the like. It is noted that the meteris optional in that a separate meter can be used and the glucose datadownloaded or input by a user into the receiver. However the illustratedembodiments show an integrated system that exploits the advantagesassociated with integration of the single point glucose monitor with thereceiver 14 and delivery device 16.

FIGS. 5 to 8 are perspective views of integrated receivers including asingle point glucose monitor. It is noted that the integrated singlepoint glucose monitor can be integral with, detachably connected to,and/or operably connected (wired or wireless) to the receiver 14 andmedicament delivery device 16. The single point glucose monitor 18integrates rapid and accurate measurement of the amount of glucose in abiological fluid and its associated processing with the calibration,validation, other processes associated with the continuous receiver 14,such as described in more detail with reference to U.S. PatentPublication No. US-2005-0154271-A1 which is incorporated herein byreference in its entirety.

In the illustrated embodiments, the single point glucose monitor 18,such as described in the above-cited U.S. Patent Publication No.US-2005-0154271-A1, includes a body 62 that houses a sensing region 64,which includes a sensing membrane located within a port. A shuttlemechanism 66 can be provided that preferably feeds a single-usedisposable bioprotective film that can be placed over the sensing region64 to provide protection from contamination. The sensing region includeselectrodes, the top ends of which are in contact with an electrolytephase (not shown), which is a free-flowing fluid phase disposed betweenthe sensing membrane and the electrodes. The sensing region measuresglucose in the biological sample in a manner such as described in moredetail above, with reference the continuous glucose sensor, and asdescribed in U.S. Pat. No. 4,994,167 and U.S. Pat. No. 4,757,022. Thesimilarity of the measurement technologies used for the continuousglucose sensor and the single point glucose sensor provides an internalcontrol that creates increased reliability by nature of consistency anddecreased error potential that can otherwise be increased due tocombining dissimilar measurement techniques. Additionally, the disclosedsensing membrane is known to provide longevity, repeatability, and costeffectiveness, for example as compared to single use strips, or thelike. However, other single point glucose monitors can be used with thepreferred embodiments.

In one alternative embodiment, the single point glucose monitorcomprises an integrated lancing and measurement device such as describedin U.S. Pat. No. 6,607,658.

In another alternative embodiment, the single point glucose monitorcomprises a near infrared device such as described in U.S. Pat. No.5,068,536. In another alternative embodiment, the single point glucosemonitor comprises a reflectance reading apparatus such as described inU.S. Pat. No. 5,426,032. In another alternative embodiment, the singlepoint glucose monitor comprises a spectroscopic transflectance devicesuch as described in U.S. Pat. No. 6,309,884. Each of the above patentsand patent applications is incorporated in its entirety herein byreference.

In some embodiments, the single point glucose meter further comprises auser interface that includes a display 72 and a button 74; however, someembodiments utilize the display 48 and buttons 50 of the receiver 14rather than providing a separate user interface for the monitor 18. Insome embodiments the single point glucose monitor measured glucoseconcentration, prompts, and/or messages can be displayed on the userinterface 48 or 72 to guide the user through the calibration and samplemeasurement procedures, or the like. In addition, prompts can bedisplayed to inform the user about necessary maintenance procedures,such as “Replace Sensor” or “Replace Battery.” The button 74 preferablyinitiates the operation and calibration sequences. The button can beused to refresh, calibrate, or otherwise interface with the single pointglucose monitor 18 as is appreciated by one skilled in the art.

Integrated Electronics

FIG. 9 is a block diagram that illustrates integrated system electronicsin one embodiment. One embodiment is described wherein the processormodule within the receiver performs much of the processing, however itis understood that all or some of the programming and processingdescribed herein can be accomplished within the continuous glucosesensor, the receiver, the single point glucose monitor, and/or thedelivery device, or any combination thereof. Similarly, displays,alarms, and other user interface functions can be incorporated into anyof the individual components of the integrated delivery device.

A quartz crystal 76 is operably connected to an RF module 78 thattogether function to receive and synchronize data streams via an antenna80 (for example, transmission 40 from the RF module 44 shown in FIG. 3).Once received, a processor module 82 processes the signals, such asdescribed below. However, other methods of wired or wirelesscommunication can be substituted for the RF communication describedherein.

The processor module 82 is the central control unit that provides theprocessing for the receiver, such as storing data, analyzing continuousglucose sensor data stream, analyzing single point glucose values,accuracy checking, checking clinical acceptability, calibrating sensordata, downloading data, recommending therapy instructions, calculatingmedicament delivery amount, type and time, learning individual metabolicpatterns, and controlling the user interface by providing prompts,messages, warnings and alarms, or the like. The processor module 82 caninclude all or part of the controller module, as described elsewhereherein, and with reference to FIGS. 13 to 17, for example. The processormodule 82 can include hardware and software that performs the processingdescribed herein, including for example, read only memory 84 (ROM), suchas flash memory, provides permanent or semi-permanent storage of data,storing data such as sensor ID, receiver ID, and programming to processdata streams (for example, programming for performing estimation andother algorithms described elsewhere herein), and random access memory88 (RAM) stores the system's cache memory and is helpful in dataprocessing. For example, the RAM 88 stores information from thecontinuous glucose sensor, delivery device, and/or single point glucosemonitor for later recall by the user or a doctor; a user or doctor cantranscribe the stored information at a later time to determinecompliance with the medical regimen or evaluation of glucose response tomedication administration (for example, this can be accomplished bydownloading the information through the pc com port 90). In addition,the RAM 88 can also store updated program instructions and/or hostspecific information. FIGS. 10 and 11 describe more detail aboutprogramming that is preferably processed by the processor module 82. Insome alternative embodiments, memory storage components comparable toROM and RAM can be used instead of or in addition to the preferredhardware, such as SRAM, EEPROM, dynamic RAM, non-static RAM, rewritableROMs, flash memory, or the like.

In some embodiments, the processor module 82 monitors the internallyderived data (e.g., the continuous glucose sensor data stream) 40 todetermine a preferable time for capturing glucose concentration valuesusing the single point glucose monitor electronics 116 for calibrationof the continuous sensor data stream. For example, when sensor glucosedata (for example, observed from the data stream) changes too rapidly, asingle point glucose monitor reading may not be sufficiently reliablefor calibration during unstable glucose changes in the host; incontrast, when sensor glucose data are relatively stable (for example,relatively low rate of change), a single point glucose monitor readingcan be taken for a reliable calibration. In some additional embodiments,the processor module can prompt the user via the user interface toobtain a single point glucose value for calibration at predeterminedintervals. In some additional embodiments, the user interface can promptthe user to obtain a single point glucose monitor value for calibrationbased upon certain events, such as meals, exercise, large excursions inglucose levels, faulty or interrupted data readings, or the like. Insome embodiments, certain acceptability parameters can be set forreference values received from the single point glucose monitor. Forexample, in one embodiment, the receiver only accepts reference glucosedata between about 40 and about 400 mg/dL.

In some embodiments, the processor module 82 monitors the internallyderived data, such as but not limited to the continuous glucose sensordata stream, to determine a preferable time for medicament delivery,including type, amount, and time. In some embodiments, the processormodule is programmed to detect impending clinical risk and can requestdata input, a reference glucose value from the single point glucosemonitor, or the like, in order to confirm a therapy recommendation. Insome embodiments, the processor module is programmed to processinternally derived data and medicament therapies to adaptive adjust toan individual's metabolic patterns. In some embodiments, the processormodule is programmed to project glucose trends based on data from theintegrated system (for example, medicament delivery information, userinput, or the like). In some embodiments, the processor module isprogrammed to calibrate the continuous glucose sensor based on theintegrated single point glucose monitor. Numerous other programming canbe incorporated into the processor module, as is appreciated by oneskilled in the art, as is described in cited patents and patentapplications here, and as is described with reference to flowcharts ofFIGS. 10 to 12.

It is noted that one advantage of integrated system of the preferredembodiments can be seen in the time stamp of the sensor glucose data,medicament delivery data, and reference glucose data. Namely, typicalimplementations of the continuous glucose sensor 12, wherein themedicament delivery 16 and/or single point glucose monitor 18 is notintegral with the receiver 14, the reference glucose data or medicamentdelivery data can be obtained at a time that is different from the timethat the data is input into the receiver 14. Thus, the user may notaccurately input the “time stamp” of the delivery or, for example, thetime or obtaining reference glucose value or administering themedicament, at the time of reference data input into the receiver.Therefore, the accuracy of the calibration of the continuous sensor,prediction of glucose values, therapy recommendations, and otherprocessing is subject to human error (for example, due toinconsistencies in entering the actual time of the single point glucosetest). In contrast, the preferred embodiments of the integrated systemadvantageously do no suffer from this potential inaccuracy when the timestamp is automatically and accurately obtained at the time of the event.Additionally, the processes of obtaining reference data andadministering the medicament can be simplified and made convenient usingthe integrated receiver because of fewer loose parts (for example,cable, test strips, etc.) and less required manual data entry.

A battery 92 is operably connected to the processor module 82 andprovides power for the receiver. In one embodiment, the battery is astandard AAA alkaline battery, however any appropriately sized andpowered battery can be used. In some embodiments, a plurality ofbatteries can be used to power the system. In some embodiments, a powerport (not shown) is provided permit recharging of rechargeablebatteries. A quartz crystal 94 is operably connected to the processormodule 168 and maintains system time for the computer system as a whole.

A PC communication (com) port 90 can be provided to enable communicationwith systems, for example, a serial communications port, allows forcommunicating with another computer system (for example, PC, PDA,server, and the like). In one exemplary embodiment, the receiver is ableto download historical data to a physician's PC for retrospectiveanalysis by the physician. The PC communication port 90 can also be usedto interface with other medical devices, for example pacemakers,implanted analyte sensor patches, infusion devices, telemetry devices,and the like.

A user interface 96 comprises a keyboard 98, speaker 100, vibrator 102,backlight 104, liquid crystal display (LCD) 106, one or more buttons108, and/or a scroll wheel (not shown). The components that comprise theuser interface 96 provide controls to interact with the user. Thekeyboard 98 can allow, for example, input of user information abouthimself/herself, such as mealtime, exercise, insulin administration, andreference glucose values. The speaker 100 can provide, for example,audible signals or alerts for conditions such as present and/orpredicted hyper- and hypoglycemic conditions. The vibrator 102 canprovide, for example, tactile signals or alerts for reasons such asdescribed with reference to the speaker, above. The backlight 104 can beprovided, for example, to aid the user in reading the LCD in low lightconditions. The LCD 106 can be provided, for example, to provide theuser with visual data output. In some embodiments, the LCD is atouch-activated screen. The buttons 108 can provide for toggle, menuselection, option selection, mode selection, and reset, for example. Insome alternative embodiments, a microphone can be provided to allow forvoice-activated control.

The user interface 96, which is operably connected to the processormodule 82, serves to provide data input and output for both thecontinuous glucose sensor, delivery mechanism, and/or for the singlepoint glucose monitor. Data output includes a numeric estimated analytevalue, an indication of directional trend of analyte concentration, agraphical representation of the measured analyte data over a period oftime, alarms/alerts, therapy recommendations, actual therapyadministered, event markers, and the like. In some embodiments, theintegrated electronics are configured to display a representation of atarget glucose value or target glucose range on the user interface. Someadditional data representations are disclosed in U.S. Patent PublicationNo. US-2005-0203360-A1, which is incorporated herein by reference in itsentirety.

In some embodiments, prompts or messages can be displayed on the userinterface to guide the user through the initial calibration and samplemeasurement procedures for the single point glucose monitor.Additionally, prompts can be displayed to inform the user aboutnecessary maintenance procedures, such as “Replace Sensing Membrane” or“Replace Battery.” Even more, the glucose concentration value measuredfrom the single point glucose monitor can be individually displayed.

In some embodiments, prompts or messages can be displayed on the userinterface to convey information to the user, such as malfunction,outlier values, missed data transmissions, or the like, for thecontinuous glucose sensor. Additionally, prompts can be displayed toguide the user through calibration of the continuous glucose sensor.Even more, calibrated sensor glucose data can be displayed, which isdescribed in more detail with reference to U.S. Patent Publication No.US-2005-0027463-A1 and U.S. Patent Publication No. US-2005-0203360-A1,each of which is incorporated herein by reference in its entirety.

In some embodiments, prompts or messages about the medicament deliverydevice can be displayed on the user interface to inform or confirm tothe user type, amount, and time of medicament delivery. In someembodiments, the user interface provides historical data and analytespattern information about the medicament delivery, and the host'smetabolic response to that delivery, which may be useful to a host ordoctor in determining the level of effect of various medicaments.

Electronics 110 associated with the delivery device 16 (namely, thesemi-automated and automated delivery devices) are operably connected tothe processor module 82 and include a processor module 112 forprocessing data associated with the delivery device 16 and include atleast a wired or wireless connection (for example, RF module) 114 fortransmission of data between the processor module 82 of the receiver 14and the processor module 112 of the delivery device 16. Otherelectronics associated with any of the delivery devices cited herein, orother known delivery devices, may be implemented with the deliverydevice electronics 110 described herein, as is appreciated by oneskilled in the art.

In some embodiments, the processor module 112 comprises programming forprocessing the delivery information in combination with the internallyderived data (e.g., continuous sensor information). In some embodiments,the processor module 112 includes all or part of the controller module,as described elsewhere herein. In some alternative embodiments, theprocessor module 82 comprises programming for processing the deliveryinformation in combination with the internally derived data. In someembodiments, both processor modules 82 and 112 mutually processinformation related to each component.

In some embodiments, the medicament delivery device 16 further includesa user interface (not shown), which may include a display and/orbuttons, for example. U.S. Pat. No. 6,192,891, U.S. Pat. No. 5,536,249,and U.S. Pat. No. 6,471,689 describe some examples of incorporation of auser interface into a medicament delivery device, as is appreciated byone skilled in the art.

Electronics 116 associated with the single point glucose monitor 18 areoperably connected to the processor module 120 and include apotentiostat 118 in one embodiment that measures a current flow producedat the working electrode when a biological sample is placed on thesensing membrane, such as described above. The current is then convertedinto an analog signal by a current to voltage converter, which can beinverted, level-shifted, and sent to an A/D converter. The processormodule can set the analog gain via a control port (not shown). The A/Dconverter is preferably activated at one-second intervals. The processormodule evaluates the converter output with any number of patternrecognition algorithms known to those skilled in the art until a glucosepeak is identified. A timer is then preferably activated for about 30seconds at the end of which time the difference between the first andlast electrode current values is calculated. This difference is thendivided by the value stored in the memory during instrument calibrationand is then multiplied by the calibration glucose concentration. Theglucose value in milligram per deciliter, millimoles per liter, or thelike, is then stored in the processor module, displayed on the userinterface, used to calibrate of the glucose sensor data stream,downloaded, etc.

Programming and Processing

FIG. 10 is a flow chart that illustrates the process 130 of validatingtherapy instructions prior to medicament delivery in one embodiment. Insome embodiments, the therapy recommendations include a suggestion onthe user interface of time, amount, and type of medicament to delivery.In some embodiments, therapy instructions include calculating a time,amount, and/or type of medicament delivery to administer, and optionallytransmitting those instructions to the delivery device. In someembodiments, therapy instructions include that portion of a closed loopsystem wherein the determination and delivery of medicament isaccomplished, as is appreciated by one skilled in the art.

Although computing and processing of data is increasingly complex andreliable, there are circumstances by which the therapy recommendationsnecessitate human intervention. Some examples include when a user isabout to alter his/her metabolic state, for example due to behavior suchas exercise, meal, pending manual medicament delivery, or the like. Insuch examples, the therapy recommendations determined by the programmingmay not have considered present or upcoming behavior, which may changethe recommended therapy. Numerous such circumstances can be contrived;suffice it to say that a validation may be advantageous in order toensure that therapy recommendations are appropriately administered.

At block 132, a sensor data receiving module, also referred to as thesensor data module, receives sensor data (e.g., a data stream),including one or more time-spaced sensor data points, from a sensor viathe receiver, which may be in wired or wireless communication with thesensor. The sensor data point(s) may be raw or smoothed, such asdescribed in U.S. Patent Publication No. US-2005-0043598-A1 which isincorporated herein by reference in its entirety.

At block 134, a medicament calculation module, which is a part of aprocessor module, calculates a recommended medicament therapy based onthe received sensor data. A variety of algorithms may be used tocalculate a recommended therapy as is appreciated by one skilled in theart.

At block 136, a validation module, which is a part of the processormodule, optionally validates the recommended therapy. The validation mayinclude a request from the user, or from another component of theintegrated system 10, for additional data to ensure safe and accuratemedicament recommendation or delivery. In some embodiments, thevalidation requests and/or considers additional input, such as time ofday, meals, sleep, calories, exercise, sickness, or the like. In someembodiments, the validation module is configured to request thisinformation from the user. In some embodiments, the validation module isresponsive to a user inputting such information.

In some embodiments, when the integrated system 10 is in fully automatedmode, the validation module is triggered when a potential risk isevaluated. For example, when a clinically risky discrepancy isevaluated, when the acceleration of the glucose value is changing or islow (indicative of a significant change in glucose trend), when it isnear a normal meal, exercise or sleep time, when a medicament deliveryis expected based on an individual's dosing patterns, and/or a varietyof other such situations, wherein outside influences (meal time,exercise, regular medicament delivery, or the like) may deemconsideration in the therapy instructions. These conditions fortriggering the validation module may be pre-programmed and/or may belearned over time, for example, as the processor module monitors andpatterns an individual's behavior patterns.

In some embodiments, when the integrated system 10 is in semi-automatedmode, the system may be programmed to request additional informationfrom the user regarding outside influences unknown to the integratedsystem prior to validation. For example, exercise, food or medicamentintake, rest, or the like may input into the receiver for incorporationinto a parameter of the programming (algorithms) that processing thetherapy recommendations.

At block 138, the receiver confirms and sends (for example, displays,transmits and/or delivers) the therapy recommendations. In manualintegrations, the receiver may simply confirm and display therecommended therapy, for example. In semi-automated integrations, thereceiver may confirm, transmit, and optionally delivery instructions tothe delivery device regarding the recommended therapy, for example. Inautomated integrations the receiver may confirm and ensure the deliveryof the recommended therapy, for example. It is noted that these examplesare not meant to be limiting and there are a variety of methods by whichthe receiver may confirm, display, transmit, and/or deliver therecommended therapy within the scope of the preferred embodiments.

FIG. 11 is a flow chart 140 that illustrates the process of providingadaptive metabolic control using an integrated system in one embodiment.In this embodiment, the integrated system is programmed to learn thepatterns of the individual's metabolisms, including metabolic responseto medicament delivery.

At block 142, a medicament data receiving module, which may beprogrammed within the receiver 14 and/or medicament delivery device 16,receives medicament delivery data, including time, amount, and/or type.In some embodiments, the user is prompted to input medicament deliveryinformation into the user interface. In some embodiments, the medicamentdelivery device 16 sends the medicament delivery data to the medicamentdata-receiving module.

At block 144, a sensor data receiving module, also referred to as thesensor data module, receives sensor data (e.g., a data stream),including one or more time-spaced sensor data points, from a sensor viathe receiver, which may be in wired or wireless communication with thesensor.

At block 146, the processor module, which may be programmed into thereceiver 14 and/or the delivery device 16 is programmed to monitor thesensor data from the sensor data module 142 and medicament delivery fromthe medicament delivery module 144 to determine an individual'smetabolic profile, including their response to various times, amounts,and/or types of medicaments. The processor module uses any patternrecognition-type algorithm as is appreciated by one skilled in the artto quantify the individual's metabolic profile.

At block 148, a medicament calculation module, which is a part of aprocessor module, calculates the recommended medicament based on thesensor glucose data, medicament delivery data, and/or individual'smetabolic profile. In some embodiments, the recommended therapy isvalidated such as described with reference to FIG. 10 above. In someembodiments, the recommended therapy is manually, semi-automatically, orautomatically delivered to the host.

At block 150, the process of monitoring and evaluation a host'smetabolic profile is repeated with new medicament delivery data, whereinthe processor monitors the sensor data with the associated medicamentdelivery data to determine the individual's metabolic response in orderto adaptively adjust, if necessary, to newly determined metabolicprofile or patterns. This process may be continuous throughout the lifeof the integrated system, may be initiated based on conditions met bythe continuous glucose sensor, may be triggered by a host or doctor, ormay be provided during a start-up or learning phase.

While not wishing to be bound by theory, it is believed that byadaptively adjusting the medicament delivery based on an individual'smetabolic profile, including response to medicaments, improved long-termhost care and overall health can be achieved.

FIG. 12 is a flow chart 152 that illustrates the process of glucosesignal estimation using the integrated sensor and medicament deliverydevice in one embodiment. It is noted that glucose estimation and/orprediction are described in U.S. Patent Publication No.US-2005-0027463-A1 and U.S. Patent Publication No. US-2005-0203360-A1,each of which has been incorporated herein by reference in its entirety.However, the preferred embodiments described herein, furtherincorporated additional data of medicament delivery in estimating orpredicting glucose trends.

At block 154, a sensor data receiving module, also referred to as thesensor data module, receives sensor data (e.g., a data stream),including one or more time-spaced sensor data points, from a sensor viathe receiver, which may be in wired or wireless communication with thesensor.

At block 156, the medicament data receiving module, which may beprogrammed within the receiver 14 and/or medicament delivery device 16,receives medicament delivery data, including time, amount, and/or type.

At block 158, the processor module evaluates medicament delivery datawith substantially time corresponding glucose sensor data to determineindividual metabolic patterns associated with medicament delivery.“Substantially time corresponding data” refers to that time periodduring which the medicament is delivered and its period of release inthe host.

At block 160, the processor module estimates glucose values responsiveto individual metabolic patterns associated with the medicamentdelivery. Namely, the individual metabolic patterns associated with themedicament delivery are incorporated into the algorithms that estimatepresent and future glucose values, which are believed to increaseaccuracy of long-term glucose estimation.

FIG. 13 is a flow chart 200 that illustrates the process of determiningmedicament delivery using an integrated system 10, in one embodiment. Inpreferred embodiments, medicament (e.g., insulin or another drug)delivery is calculated to maintain the host substantially at and/orwithin a target range. In the case of insulin therapy, the target rangeis generally a range of preferred glucose concentrations within whichthe host is to maintain (at least to try) his blood sugar, as isdiscussed below. For example, in some circumstances, the target range isa range of euglycemic glucose concentrations. As is understood by thoseskilled in the art, glycemic ranges can vary, depending upon the therapygoals and the morbidity/mortality associated with a given glucose level(e.g., concentration). For example, according to the American DiabetesAssociation, a preferred target range is a euglycemic range thatprovides tight glucose control and substantially reduces diabeticmorbidity and mortality, namely a fasting glucose of from 90 mg/dl to130 mg/dl. Alternative target ranges can be used, such as from about 70,80, 90, 100, 110 or 120 mg/dl to about 110, 120, 130, 140, 150 or 160mg/dl or more. In some circumstances, the target range can be very wide(e.g., from about 80 mg/dl to about 160 mg/dl) or very narrow (e.g., 90mg/dl to 120 mg/dl) or even a single glucose concentration. In someembodiments, the host and/or his health care professional select atarget range. In some embodiments, the target range is programmable(e.g., pre-programmable, re-programmable), such as by the host, acaretaker of the host or the manufacturer. In some embodiments, theintegrated system includes two or more target ranges. In someembodiments, the controller module is configured toadaptively/intelligently program (e.g., re-program) the target range,such as after evaluation of the internally derived data and the host'smetabolic response to insulin therapy.

At block 202, the processor module is configured to receive and processinternally derived data. Internally derived data can include but it notlimited to continuous glucose sensor data, continuous glucose processedsensor data, auxiliary sensor data, processed auxiliary sensor data,delivery device data and processed delivery device data, includingglucose concentration, glucose concentration range, change in glucoseconcentration, glucose concentration rate of change, acceleration of theglucose concentration rate of change, host insulin sensitivity, changein host insulin sensitivity, host metabolic response to insulin therapy,amount of insulin delivered, time of insulin delivery, insulin on board,time, acceleration, host activity level, pressure, a pH, a temperature,an oxygen level, the level of an analyte other than glucose, a proximityand orientation. In some embodiments, internally derived data caninclude data derived from algorithmic processing of continuous analytesensor data and/or auxiliary sensor data and/or medicament deliverydevice data. In some embodiments, the system is configured to furtherreceived external data (e.g., meal occurrence/content, exercise, unitsof insulin delivered, time of insulin delivery, etc.) such as forhistorical purposes (e.g., as a diary or log).

At block 204, the system is configured to calculate (e.g., determine) amedicament therapy (e.g., insulin therapy) based solely on internallyderived data and any constraint (e.g., range, boundary, profile and thelike). In general, calculation of the medicament therapy is conducted bythe system's controller module (e.g., on/off, dynamic basal and/ordynamic bolus controller module), as described elsewhere herein. In someembodiments, evaluation and calculation is iterative. In someembodiments, the calculated insulin therapy includes an instruction fordelivery of the insulin therapy to the host.

At block 206, the system is optionally configured to validate thecalculated therapy based on patient (e.g., host) input. For example, insome embodiments, the host must accept the calculated medicament therapybefore the system can proceed to providing (e.g., delivering) themedicament therapy at block 208, and the system can return to block 202.If the host accepts calculated the medicament therapy (e.g., the dose isvalidated), the medicament therapy will be provided/delivered.Similarly, if the host does not accept the medicament therapy, nomedicament will be given. In some embodiments, the system is configuredsuch that the host can command the system to provide a manuallycalculated dose (e.g., calculated by the host). In some embodiments, thesystem is further configured to allow the system to adaptively andintelligently determine an appropriate and/or optimal delivery schedulefor the commanded manually calculated dose.

At block 208, the system is configured to deliver the calculated insulintherapy, as described elsewhere herein. In some embodiments, the insulindelivery device is configured to deliver the calculated insulin therapyautomatically upon receipt of an instruction from the controller module.After delivering the insulin therapy, the system is configured to returnto block 202.

FIG. 14 is a flow chart 204 that illustrates calculation of a medicamenttherapy based on the internally derived data, in one embodiment.Generally, the system 10 is configured to use at least one controllermodule (all or in part) to calculate the insulin therapy, such as butnot limited to an on/off controller module 210, a dynamic basalcontroller module 212 and a dynamic bolus controller module 214. In someembodiments, the system is configured with only one controller module.In other embodiments, the system is configured with two or all three ofthe controller modules. In one embodiment, the system includes two ormore controller modules configured to work in concert (e.g., inconjunction, together, in combination). In some embodiments, thecontroller module is configured to provide all or some of the processingfor block 204 of FIG. 13. The controller module can be incorporated intoany portion of the integrated system, such as but not limited to thereceiver, the medicament delivery device, a component separate from thereceiver and the delivery device, or a combination thereof (e.g.,integrated electronics, such as a processor module). In someembodiments, a controller module is included in processor module 82and/or in processor module 112.

On/Off Controller Module

FIG. 15 is a flow chart that illustrates an on/off controller module210, in one embodiment.

At block 216, the on/off controller module is configured tointelligently, adaptively and iteratively evaluate the internallyderived data (e.g., raw and/or processed glucose sensor data) relativeto a target range and/or a glucose boundary. In some embodiments, aglucose boundary is a host glucose concentration at which the system isconfigured to deliver insulin. In some embodiments, the target range andthe glucose boundary are associated with each other. For example, theglucose boundary can be the upper limit of the target range. In someembodiments, the host does not validate either data or a calculatedmedicament therapy. In preferred embodiments, the system includes acontinuous analyte sensor, and can include one or more auxiliarysensors, such as described elsewhere herein. In some embodiments, theglucose boundary can be programmable, such as by the host, a caretakerof the host and/or the manufacturer. In some embodiments, the glucoseboundary is programmable by an intelligent/adaptive controller module.

At block 218, the on/off controller module is configured to actuatemedicament delivery, such as by selecting between on and offinstructions. The point at which the selection is made can be referredto as a setpoint. In some embodiments, the set point is the glucoseboundary. In one exemplary embodiment, the system includes programmingto select between the on and off instructions. When evaluation of theinternally derived data indicates that the host's glucose is (or has)surpassing (or surpassed) a glucose boundary, the controller moduleselects the on instruction, which directs actuation of the insulindelivery device (e.g., turns on delivery). Conversely, when the host'sglucose falls below a glucose boundary (as determined by evaluation ofthe internally derived data), the off instruction is selected andinsulin delivery is terminated (e.g., turned off). In preferredembodiments, the insulin will be delivered at a programmable rate, whichcan be programmed by the host, a caretaker of the host, or themanufacturer, for example. In some embodiments, the on/off controllercan include more than one setpoint, such as but not limited to a firstset point to select the on instruction and a second setpoint to selectthe off instruction.

In some embodiments, the on/off controller module is configured toadjust the insulin delivery rate in response to evaluation of internallyderived data and the host's metabolic response to insulin delivery(e.g., metabolic state). For example, the insulin can be delivered atrelatively faster or slower rates, depending upon the evaluation of theinternal data. In some circumstances, when the on instruction isselected, the medicament can be delivered substantially continuouslyand/or intermittently, such as but not limited to at a single rate(e.g., about 0.05 U, 0.1 U, 0.2 U, 0.3 U, 0.4 U, 0.5 U, 0.6 U, 0.7 U,0.8 U or 0.9 U per hour or more).

In one exemplary embodiment, the integrated system 10 includes an on/offcontroller module configured to intelligently and adaptively evaluatethe internally derived data relative to a programmed glucose boundaryand then select between the on and off instructions. For example, if theglucose boundary is 140 mg/dl, then the controller module evaluates theinternally derived data against the 140 mg/dl glucose boundary (block216). If the host's glucose is above the 140 mg/dl glucose boundary,then the controller module selects the on instruction, which leads toactuation of insulin delivery at box 218. If the host's glucose is abovethe 140 mg/dl glucose boundary and insulin is currently being delivered(e.g., the on instruction was selected at an earlier time), then thecontroller module does nothing (e.g., insulin continues to bedelivered). If the host's glucose is 140 mg/dl or less, the offinstruction is selected (or the on instruction isde-selected/terminated), whereby insulin delivery is ceased. In someembodiments, the insulin is delivered (e.g., infused) substantiallycontinuously, such as at a given rate (e.g., U/min), or substantiallyintermittently, such as small volumes every few minutes (e.g., 0.5-Uevery 6-minutes). In preferred embodiments, the system is configured,such that data evaluation and/or insulin delivery are iterative (e.g.,cyclic, periodic, continuous, automatic, and the like). Because theysystem is configured to function intelligently and adaptively, in someembodiments, the system can modify (e.g., adjust, either with or withouthost validation) the glucose boundary and/or the insulin infusion rate,such that maintenance of the host within the target range is optimized.

In another exemplary embodiments, the system 10 includes an on/offcontroller module configured for use in combination with flash insulin.The flash insulin therapy can be delivered automatically, periodically,intermittently and/or substantially continually, in response to theon/off controller, such that the host is maintained substantially atand/or within the target range. For example, in some embodiments, thesystem is configured to intermittently deliver small doses of flashinsulin when (while) the host's glucose is above the glucose boundary.The rate of flash insulin delivery is programmed such that when thehost's glucose is rising and surpasses the glucose boundary, the oninstruction is selected and a small amount of flash insulin isdelivered. After delivery, the controller module can be configured towait a brief period (e.g., a few minutes), and then evaluate theinternally derived data relative the glucose boundary. If the internallyderived data indicates that the host's glucose is still above theglucose boundary, then another small dose of flash insulin can bedelivered. Alternatively, the system can be configured to wait until thedelivered insulin has had a predetermined effect (e.g., time sufficientfor the activity of about 50, 60, 70, 80, 90 or 95% of the deliveredinsulin to peak, or for the activity of about 50, 60, 70, 80, 90 or 95%of the delivered insulin to terminate), prior to returning to block 202(FIG. 13). As is appreciated by one skilled in the art, the system canbe configured to proceed through several cycles of these steps (e.g.,iteratively evaluate and provide insulin doses using the on/offcontroller module), until the host's glucose level falls to/below theglucose boundary. When the host's glucose level falls to/below theglucose boundary, the on/off controller is configured to select the offinstruction, which results in termination of insulin delivery. While notwishing to be bound by theory, it is believed that use of flash insulinin combination with an on/off controller module advantageouslysubstantially prevents stacking of insulin doses and substantiallyavoids hypoglycemic episodes. Accordingly, improved host health andsafety are promoted while diabetic complications are avoided or delayedduring the host's lifetime.

In some embodiments, the integrated system is configured arranged foruse with other insulins (e.g., regular (e.g., wild type), fast-acting orrapid-acting human insulin analogs, etc.), such that the on/offcontroller evaluates/tracks “insulin on-board” (e.g., the total amountof active insulin currently in the host's body).

Dynamic Basal Controller Module

As is understood by one skilled in the art, insulin needs vary betweenindividuals and through out the day, both during and between meals. Totake care of between meal glucose fluctuations, diabetic hosts generallyemploy a basal schedule (e.g., basal profile) for continuous delivery oflow levels of insulin, such that, between meals, the host's glucose isrelatively steady (e.g., remains within a target (e.g., euglycemic)range). Accordingly, in preferred embodiments, the integrated system 10includes a dynamic basal controller module configured to iterativelyevaluate internally derived data relative to a programmable basalprofile and iteratively calculate a dynamic basal insulin therapy withinthe basal profile.

FIG. 16 is a flow chart that illustrates a dynamic basal controllermodule 212, in one embodiment. In preferred embodiments, the dynamicbasal controller module can be part of the electronics module and isconfigured to evaluate internally derived data relative to a basalprofile 220 and to intelligently and adaptively calculate a dynamicbasal medicament therapy 222, based on that evaluation. In preferredembodiments, the insulin therapy is determined solely on internallyderived data and the basal profile.

A basal profile generally includes a schedule of time blocks, each blockbeing associated with an insulin delivery rate. In general, a diabetichost can determine his basal profile by experimentation. For example,the basal insulin delivery rate for a particular time period can bedetermined by fasting while periodically evaluating the glucose level.Neither food nor bolus insulin can be taken for 4-hours prior to orduring the evaluation period. If the blood sugar level changesdramatically during evaluation, then the basal rate can be adjusted toincrease or decrease insulin delivery to keep the blood sugar levelapproximately steady. For instance, to determine the host's morningbasal requirement, he must skip breakfast. On waking, he would test hisglucose level periodically until lunch. Changes in blood glucose levelare compensated with adjustments in the morning basal rate. The processis repeated over several days, varying the fasting period, until a24-hour basal profile (which keeps fasting blood sugar levels relativelysteady) has been built up. As used herein, a basal profile includes aschedule of one or more time blocks, wherein each time block isassociated with a maximum insulin delivery rate. As is described herein,in some embodiments, the dynamic basal controller module is constrainedby the basal profile. Accordingly, in some embodiments, the controllermodule is configured to evaluate internally derived data (e.g.,including re-evaluate internally derived data as it is received) and toiteratively calculate an insulin delivery rate (e.g., insulin therapy)up to the maximum rate of a current time block. Accordingly, the insulintherapy can include a delivery rate less than the maximum insulindelivery rate associated with the current time block. In someembodiments, the basal profile includes a 24-hour schedule. In someembodiments, the schedule can be shorter or longer than 24-hours. Insome embodiments, the schedule is repeatable and/or cyclic (e.g.,iterative). In some embodiments, the host, a caretaker of the host,and/or the manufacturer can program a basal profile. In somecircumstances, an intelligent/adaptive controller module can beconfigured to program the basal profile.

At block 220, in preferred embodiments, the dynamic basal controllermodule is configured to evaluate solely internally derived data (e.g.,from an operably connect continuous glucose sensor, from an auxiliarysensor and/or an insulin delivery device) relative to a programmed basalprofile. Internally derived data includes but is not limited to glucoseconcentration, change in concentration, rate of change of concentration,acceleration (or deceleration) of the change, direction of the change,predicted analyte concentration for a future time, estimated analyteconcentration, possible variations of analyte data (e.g., based onmaximum possible error), trend information and the like. For example, insome circumstances, a low rate of change (in glucoseconcentration/level) is from about ±0 mg/dl/min to about 1 mg/dl/min, amoderate rate of change is from about 1 mg/dl/min to about 2 mg/dl/min,and a high rate of change is from about 3 mg/dl/min to about 6mg/dl/min. In some embodiments, the calculation can include evaluationof the host's metabolic response to insulin therapy, which can dependupon a variety of factors, such as but not limited to the type ofinsulin delivered, the mode and/or location of delivery, and the like.

In some embodiments, internally derived data can include data receivedfrom one or more auxiliary sensors, such as but not limited to sensorsfor glucose, an analyte other than glucose, pH, temperature, pressure,host movement, host body position, proximity, and the like. For example,an accelerometer can provide data regarding the host's activity level(e.g., sedentary versus exercising versus sleeping), which can affectthe host's insulin requirement. In one exemplary embodiment, the dynamicbasal controller module is configured to evaluate accelerometer data inconjunction with internally derived data, depending upon if theaccelerometer data is within or without a programmed range (e.g.,whether or not the host is very active). For example, the system can beconfigured such that if the accelerometer data is above a setpoint(e.g., indicates that the host is very active or exercising), then theaccelerometer data is considered by the controller module; if theaccelerometer data is below the set point, the accelerometer is notconsidered. In one exemplary embodiment, the system is configured suchthat the basal controller module intelligently monitors the host'sactivity level (e.g., over a period of days and/or weeks) and adaptivelyadjusts the basal profile to maintain the host substantially within thetarget range during both active and inactive periods of the day. Forexample, in some embodiments, the controller module is configured tointelligently determine when the host is generally very active (e.g.,exercising), less active (e.g., working at the computer) or sedentary(e.g., sleeping). Some hosts will tend to be more active than others.Advantageously, because the controller module responds to changes in thehost's metabolic state, each host can have a basal profile optimized tohis personal needs.

At block 222, in some embodiments, the dynamic basal controller moduleis configured to calculate (e.g., determine) a dynamic basal medicamenttherapy (also referred to as the “insulin therapy”) based solely on theinternally derived data and the basal profile (e.g., the evaluationthereof), wherein the calculated insulin therapy falls within the basalprofile. The insulin therapy calculated by the dynamic basal controllermodule is a rate of insulin delivery less than or equal to the insulindelivery rate associated with the basal profile (e.g., at the currentblock of time). Preferably, the delivery rate is sufficient to bring thehost's glucose concentration substantially within a pre-programmedtarget range (e.g., a euglycemic range). Over time, the insulin therapycan include a plurality of delivery rates at different time blockscalculated to maintain the host within the target range. In someembodiments, the maximum insulin therapy (e.g., delivery rate) is fromabout 0.01 U/hour or less to about 6.0 U/hour or more. For example, insome embodiments, the maximum insulin therapy is from about 0.01 U/hr toabout 0.2 U/hr. In some embodiments, the maximum insulin therapy is fromabout 0.21 U/hr to about 0.3 U/hr. In some embodiments, the maximuminsulin therapy is from about 0.31 U/hr to about 0.4 U/hr. In someembodiments, the maximum insulin therapy is from about 0.41 U/hr toabout 0.5 U/hr. In some embodiments, the maximum insulin therapy is fromabout 0.51 U/hr to about 1.0 U/hr. In some embodiments, the maximuminsulin therapy is about 1.5 U/hr, 2.0 U/hr, 2.5 U/hr, 3.0 U/hr, 3.5U/hr, 4.0 U/hr, 4.5 U/hr, 5.0 U/hr, or 5.5 U/hr. In preferredembodiments, instructions for delivery of the calculated insulin therapyare sent to the insulin delivery device, which then automaticallydelivers the instructed insulin therapy. In some embodiments, dynamicbasal controller module can include one or more instructions forcalculation and/or delivery of the basal insulin therapy. The calculatedinsulin delivery rate can be an instruction provided to an insulindelivery device to delivery the insulin therapy, such as toautomatically deliver the therapy.

In preferred embodiments, the system 10 is configured to iteratively(e.g., cyclic, periodic, and the like) evaluate the internally deriveddata (e.g., including past and newly/more recently received internallyderived data) and to iteratively calculate an insulin delivery rate.Because the system is configured to function intelligently andadaptively, in some embodiments, the system can respond to changes inthe host's metabolic state by modifying (e.g., adjusting, programming,re-programming, either with or without host validation) the basalprofile, such that maintenance of the host within the selected targetrange is optimized. In some embodiments, the controller module includesprogramming to adjust the basal profile in response to internallyderived data and the host's metabolic response. In some embodiments, theinsulin therapy substantially maintains the host's glucose concentrationwithin the target range without driving the host into a hyper- orhypoglycemic range. In some embodiments, the dynamic basal controllermodule includes one or more instructions configured to process theinternally derived data and iteratively provide the therapyinstructions. In a further embodiment, these instructions includeinstructions for evaluating the internally derived data and calculatingthe insulin therapy based solely on the internally derived data.

In one exemplary embodiment, the integrated system includes a dynamicbasal controller module configured to iteratively (continually,automatically, periodically, or intermittently) evaluate the internallyderived data relative to a programmable basal profile and calculate aninsulin therapy that falls within the basal profile. For example, if thecurrent time block of the basal profile specifies 2 U of insulin perhour, then the controller module can calculate an insulin therapy up tothat amount. Preferably, the calculated insulin therapy is optimal formaintaining the host within the selected (e.g., preferred, engaged,programmed) target range. As the system receives additional internaldata, it is configured to adjust the insulin delivery rate in anintelligent and adaptive manner. For example, if the evaluation ofcurrently received internal data indicates that for optimal control(e.g., of blood sugar) the insulin delivery rate should be increasedfrom 0.5 U/hr to 1 U/hr, then the controller module can both sendinstructions to the integrated insulin delivery device to do so andreprogram the basal profile with the new delivery rate for that timeblock. In another example, if the evaluation might indicates that thedelivery rate should be reduced to maintain optimal control, and thenthe controller module can calculate a new insulin therapy and instructthe delivery device accordingly. Internally derived data can includetrend information, such as but not limited to changes in the host'sinsulin needs (e.g., response to delivered insulin, insulin sensitivity,or metabolic profile) over time. Accordingly, in preferred embodiments,the dynamic basal controller module is configured to evaluate this trendinformation and make intelligent adjustments to (e.g., re-program) theinsulin therapy and/or the basal profile, such that between meal glucosecontrol can be optimized (e.g., continually). In some embodiments, thesystem is configured to request validation of such a change (e.g.,re-programming) in insulin therapy and/or the basal profile.

In some embodiments, the dynamic basal controller module can beconfigured to evaluate the internally derived data 220 with respect toone or more target ranges (which can overlap) to intelligently andadaptively direct calculation of the dynamic basal medicament therapy.For example, in one exemplary embodiment, as a first step, the dynamicbasal controller module evaluates the internally derived data withrespect to glycemic ranges (e.g., hypoglycemic, euglycemic,hyperglycemic or very hyperglycemic). If, for example, the host iseuglycemic, a first calculation can be made; if the host ishyperglycemic a second calculation can be made; and if the host ishypoglycemic a third calculation can be made. In some embodiments, thecontroller evaluates the rate and/or direction of glucose concentrationchange and/or acceleration of the change (e.g., if glucose concentrationhas changed, if it is going up or down, if it is changing slowly orrapidly, etc.). For example, if the glucose level is very hyperglycemicand increasing rapidly, a first dynamic basal insulin dose (e.g., dose#1) can be calculated. If the glucose level is very hyperglycemic anddecreasing slowly, a second dynamic basal insulin dose (e.g., dose #2),which might be smaller than dose #1, can be calculated. If the glucoselevel is slightly hyperglycemic and increasing slowly, a third dynamicbasal insulin dose (dose #3) can be calculated. Dose #3 may be smallerthan both dose #1 and dose #2. If, on the other hand, the glucose levelis in the euglycemic range and decreasing slowly, insulin delivery canbe terminated (e.g., until the glucose level was again above theeuglycemic range). In another example, if the glucose level is ineuglycemic range and decreasing rapidly, or in the hypoglycemic range,the controller can be configured to alert the host, such as by an alarm,for example so that he can eat some sugar to raise his glucose level.

In some embodiments, the dynamic basal controller module is configuredfor use in conjunction with a flash-acting insulin, as describedelsewhere herein. In one exemplary embodiment, the onset of activity ofthe flash insulin is less than about 5-minutes as determined by plasmainsulin concentration according to the methods of Frohnauer et al). Insome embodiments, the flash insulin's activity peaks within about 10 to30-minutes. In some embodiments, the flash insulin's duration ofactivity is about 30-minutes or less and up to about 1-hour. In someembodiments, the flash insulin's activity peaks within about 5-minutesof delivery and terminates within about 10-20 minutes.

In some embodiments, the dynamic basal controller module is configuredfor use in conjunction with a regular, rapid-acting or fast-actinginsulin (including analogs), as described elsewhere herein. In a furtherembodiment, the dynamic basal controller module is configured to trackthe amount of insulin “on board” (e.g., the total amount of activeinsulin currently within the host and the insulin activity associatedwith that amount), and to evaluate the insulin on board when calculatinga dynamic basal therapy.

Dynamic Bolus Controller Module

Conventionally, when a host is going to eat a meal, he calculates abolus insulin dose that should be sufficient to cover the glucoseincrease anticipated due to consumption of the meal. He then giveshimself the calculated bolus dose and eats the meal. Without carefulmeasurement of carbohydrate and fat content of the meal and the host'sinsulin sensitivity, the calculated bolus dose can only estimate theamount of insulin to be taken for that meal. Thus, in general, thecalculated bolus dose will not be the optimal dose to cover the actualglucose increase that occurs when the meal is eaten. The host's sugarmay increase more than he thought it would, in which case the calculatedbolus dose could be too small, which could lead to hyperglycemia.Alternatively, the host's sugar might not rise as high as he thought itwould, in which case the calculated bolus dose may be too large, andcould lead to hypoglycemia. Accordingly, in preferred embodiments, theintegrated system 10 includes a dynamic bolus controller moduleconfigured to iteratively evaluate internally derived data relative to aprogrammable bolus constraint and iteratively calculate a dynamic bolusinsulin therapy, upon host activation of the programmable bolusconstraint.

FIG. 17 is a flow chart illustrating a dynamic bolus controller module214, in one embodiment. In preferred embodiments, the dynamic boluscontroller module is included in the electronics module and isconfigured to evaluate an engageable constraint 224 as well asinternally derived data 226. In some embodiments, the dynamic boluscontroller module is configured to intelligently provide a dynamic bolusmedicament therapy (e.g., insulin therapy) within a pre-set (e.g.,programmable) constraint 228, such as in response to the host engagingthe bolus constraint. Preferably, the dynamic bolus controller module isconfigured to iteratively calculate an insulin therapy based solely onevaluation of internally derived data (e.g., re-evaluation of internallyderived data as it is received) and the bolus constraint. In someembodiments, the dynamic bolus controller module 214 allows hostvalidation of the dynamic bolus medicament therapy (e.g., FIG. 13, box206), which is believed to promote increased user confidence, increasedhost compliance and improved health status. Advantageously, the dynamicbolus controller module 214 can be configured to use a variety ofinsulins, including but not limited to regular or rapid/quick-actinginsulins (e.g., slower onset and peak of activity, longer duration ofactivity) and flash insulins, described elsewhere herein.

In preferred embodiments, an engageable bolus constraint is associatedwith a programmable dynamic bolus insulin therapy. In preferredembodiments, the dynamic bolus insulin therapy is the maximum totalinsulin that can be delivered to the host over a specified period oftime, in response to the host engaging (e.g., selecting) the bolusconstraint associated with the insulin therapy. In some embodiments, theinsulin therapy comprises one or more portions of the maximum totalinsulin dose, as described below. In some embodiments, the bolusconstraint can be programmed (e.g., pre-programmed and/or pre-set),programmable and/or re-programmable. In some embodiments, the hostand/or a caretaker of the host can program the bolus constraint. In someembodiments, the bolus constraint can be programmed by the manufactureror the dynamic bolus controller module.

At block 224, the dynamic bolus controller module is configured toevaluate a bolus constraint (e.g., engageable/selectable, andprogrammable, re-programmable and/or pre-set limit), such as one thathas been engaged by the host. In general, a bolus constraint isassociated with an insulin therapy that has been calculated and/orestimated to be sufficient to cover an average expected rise in bloodsugar, such as an increase in glucose that occurs (on average) when ahost eats a given meal, such as but not limited to breakfast, lunch,dinner and the like. For example, on most days, the host may eat verysimilar breakfasts (e.g., an average (e.g., usual) breakfast), which cancause very similar glucose increases (e.g., an average increase inglucose). Accordingly, a “breakfast” bolus constraint can be calculatedto cover the average rise in glucose associated with an averagebreakfast. In some embodiments, a bolus constraint can be associatedwith a host activity (e.g., to cover the glucose rise associated withhost performance of about 30-minutes of vigorous exercise) or condition(e.g., a corrective bolus for when the insulin delivered is insufficientto cover an actual rise in glucose). In preferred embodiments, thesystem includes one or more selectable bolus constraints. Theconstraints can be selected by any means known in the art, such as bypushing a pre-programmed push-button or scrolling through a menu ofselectable constraints with a slider or a scroll wheel.

In some embodiments, the controller module is configured (e.g., includesprogramming) to intelligently evaluate the internally derived data andthe host's metabolic response to insulin therapy, and to adjust thebolus constraint based on that evaluation. Advantageously, a calculatedinsulin therapy is based on internally derived data, an engaged bolusconstraint and the host's metabolic response to insulin therapy, whichenables the system to optimize the insulin therapy to the host, who'smetabolic response varies over time, depending upon a variety offactors, such as but not limited to changes in the host's activitylevel, dietary changes, medications (e.g., insulin-sensitizing agents,new insulin type), and the like. Depending upon the circumstances, thecontroller module can re-program a bolus constraint by adjusting therate of insulin delivery, the amount of insulin that can be deliveredand/or the time period over which the insulin can be delivered.

At block 226, in preferred embodiments, the dynamic bolus controllermodule is configured to evaluate the internally derived data. Theinternally derived data is evaluated in the context of (e.g., relativeto) a selected bolus constraint and in response to selection(activation, engagement) of the bolus constraint. Returning to theexample of the “Breakfast” bolus constraint, in general, the host willengage the breakfast bolus constraint (e.g., by pressing apre-programmed button that is labeled “Breakfast”) at the beginning of abreakfast meal. In general, as the host consumes his breakfast, hisglucose will begin to change (e.g., rise), which the integrated system'scontinuous glucose sensor detects (e.g., measures, senses). Internallyderived data will be generated as the system's continuous glucose sensormonitors the changes in the host's glucose level. The dynamic boluscontroller module evaluates the sensor data (e.g., internally deriveddata) against (e.g., in the context of, relative to) the engagedbreakfast constraint.

At block 228, the dynamic bolus controller module calculates a dynamicbolus medicament (e.g., insulin) therapy within the selected bolusconstraint. Preferably, the dynamic bolus controller module adaptivelydetermines a substantially optimal insulin therapy, such as for example,delivery of all or a portion (e.g., in one large dose or a plurality ofsmaller doses) of the maximum total insulin dose (associated with theengaged constraint) over the specified time period. For example, if thebreakfast constraint is associated with a maximum of 10 U of insulin tobe delivered over 30-minutes, then, when the host engages the breakfastconstraint, the controller module evaluates the internally derived dataand determines an insulin therapy (including instructions sent to theinsulin delivery device, which automatically delivers the instructedinsulin therapy). For example, in some circumstances, the calculatedinsulin therapy can include delivery of the entire total dose (e.g., 10U) within the specified 30-minutes (or a shorter length of time). Inother circumstances, the calculated insulin therapy can include dividingthe total insulin therapy into two or more partial (e.g., smaller)doses, some or all of which can be delivered over the 30-minute period.Delivery of a partial dose depends upon the controller module'sevaluation of internally derived data. For example, as the 30-minutesprogress, the controller module continually (e.g., continuously,iteratively, intermittently, automatically) receives and iterativelyre-evaluates internally derived data (e.g., as it becomes available) anddetermines, based thereon, if additional partial doses are needed tohandle the rise (e.g., the actual rise) in glucose (e.g., up until themaximum dose has been delivered). In preferred embodiments, the systemis configured to slow and/or stop insulin delivery in circumstanceswherein the host is entering a severely hypoglycemic range (e.g.,programmable, such as less than about 70 mg/dl).

In one exemplary embodiment, the dynamic bolus controller module isconfigured to calculate a percentage (e.g., portion, fraction) of theengaged bolus constraint (e.g., total insulin therapy) associated with ameal. For example, if the engaged bolus constraint is programmed for atotal insulin dose (e.g., D₀) of 10 U in 1-hour, the controller modulecan calculate a first dose, such as about 7 U of insulin (e.g., dose D₁at time T₁), based on the controller module's evaluation of theinternally derived data relative to the engaged constraint. Instructionsare sent to the integrated insulin delivery device and the partial doseis automatically delivered to the host. After an appropriate waitingperiod (e.g., depending upon the insulin's TAP), the controller moduleevaluates internally derived data (e.g., at time T₂, data more recentthan data used to initially calculate D₁) and determines an additionalinsulin dose (e.g., dose D₂) required to bring the host's glucoseconcentration into a target range (at time T₂). For example, in somecircumstances, an additional insulin dose may be necessary to bring thehost's glucose concentration into the target range. In some othercircumstances, no additional doses may be required (e.g., D₂=0). Supposethat, in this example, additional insulin is required, then thecontroller module can calculate and instruct delivery of up to 2 moreunits of insulin (e.g., D₀−D₁−D₂=2 U insulin remaining). In preferredembodiments, the insulin therapy delivered to the host is smallest totalinsulin dose necessary to maintain the host substantially within thetarget range (e.g., an euglycemic range).

In some embodiments, the system is configured for user validation of thedynamic bolus therapy, such as before delivery of the insulin (e.g.,FIG. 13, box 206). In one exemplary embodiment, the system is configuredto alert the host (e.g., that a dynamic bolus therapy has beencalculated) and request host validation (e.g., that the host accepts thedynamic bolus therapy, such as a maximum amount of insulin to bedelivered over a given period of time). Upon host validation, thecalculated therapy is delivered.

In one exemplary embodiment, semi-automated integrated system 10 isconfigured such that the host can select a bolus constraint associatedwith a meal, such as by pressing one of a plurality of labeled,pre-programmed buttons or making a selection from a menu. For example,in this embodiment, each button is labeled with an icon of a food (e.g.,cereal bowl, sandwich, slice of pizza, ice cream cone) and is associatedwith an insulin therapy calculated to be sufficient to cover that food(e.g., a meal) on average. For example, the sandwich bolus constraint isassociated with an insulin dose that is generally sufficient to coverthe glucose rise associated with host consumption of an average sandwich(e.g., a maximum total of up to 10 U of insulin to be delivered over1-hour). When the host presses the sandwich button, the dynamic boluscontroller module evaluates internally derived data and intelligentlyand adaptively determines a substantially optimal way (e.g., schedule ofone or more insulin doses) to deliver a bolus insulin therapy (e.g.,constrained by the sandwich constraint), preferably such that the hostwill not substantially enter a dangerous hypoglycemic state (e.g.,glucose less than about 70 mg/dl) when the therapy is delivered. Inpreferred embodiments, the bolus controller module is configured tosubstantially continuously (e.g., constantly, automatically,iteratively, periodically, and/or intermittently) receive and evaluateinternal data and to iteratively (e.g., automatically, periodically,and/or intermittently) determine an insulin therapy. For example, insome embodiments, the bolus controller module is configured to calculatea bolus therapy (e.g., based on solely the internally derived data)every about 5, 10, 15, 20, 30, 40 or 50-minutes. In some embodiments,the bolus controller module calculates a bolus therapy about every houror longer. The calculated insulin therapy is then delivered (e.g.,administered, such as automatically) to the host. In some embodiments,the insulin therapy associated with the engaged bolus constraint can bedivided into portions (e.g., a total therapy of 10 U to be delivered in1-hour is divided into two 5 U portions, five 2 U portions, or a 5 Uportion, two 2 U portions and one 1 U portion) that can be deliveredover time period associated with the engaged bolus constraint. Ingeneral, if portions of the total bolus therapy are delivered, thecontroller module is configured to wait a period of time for thedelivered insulin to become active and to lower the host's blood sugar apre-determined amount. The length of wait varies, depending upon theinsulin's TAP and mode of delivery (e.g., injected subcutaneously by apump versus by a syringe, inhaled, and the like) or the location ofdelivery, the type of meal being consumed, the host's insulinsensitivity and metabolic state, and the like. After the wait time, thecontroller module again evaluates the internally derived data anddetermines if additional insulin is required. For example, if the host'sglucose is still increasing, another partial dose can be delivered. Thiscycle can be repeated until either the total bolus therapy has beendelivered the delivery time has expired. In some embodiments, the systemis further configured to request host validation of the therapy, such asby selection of either a YES or NO button, and the like, as isappreciated by one skilled in the art.

In some embodiments, the system is configured such that the host canmanually enter a bolus insulin dose and the dynamic bolus controllermodule can evaluate the internally derived data and determine an insulintherapy within the entered bolus dose. For example, suppose the hostwants to eat something for which there is no pre-programmed bolusconstraint, such as a candy bar. In this circumstance, the host cancalculate a bolus dose to cover the glucose increase that will probablyoccur when he eats that candy bar. He can enter the bolus dose hecalculated and then have the system monitor his glucose and deliver theentered bolus dose as necessary (e.g., based upon evaluation of theinternally derived data; to maintain and/or return the host within/to atarget range). Preferably, the calculated therapy is substantiallyoptimal for handling the glucose rise that will likely occur uponconsumption of the meal for which the host calculated the bolus dose.

In some circumstances, a selected constraint may be insufficient tohandle a meal that the host has consumed. For example, a meal can havemore carbohydrates than the average meal the engaged constraint waspre-programmed to handle. Accordingly, is the controller module can beconfigured to alert the host to a need for additional insulin. As isunderstood by one in the art, a number of alerts and/or alarms can bebuilt into the system, such as but not limited to safety alarms. Thesystem can be configured to allow the selection of an additional mealconstraint or a corrective bolus constraint and/or to allow the host toenter a manually calculated and enter a corrective bolus dose.

In preferred embodiments, the dynamic bolus controller module isconfigured to evaluate trend information (e.g., derived from theinternally derived data; the host's metabolic response to deliveredinsulin) and to adapt accordingly, such as by adjusting (e.g.,re-programming) the time and/or amount of an insulin therapy associatedwith a bolus constraint. As is understood by one skilled in the art,trend information can fluctuate over time, depending upon the host'shealth, activity level, medications consumed, and the like. In oneexemplary embodiment, the controller module is configured to evaluatethe host's insulin sensitivity over time, and to re-program a bolusconstraint such that a substantially optimal insulin therapy can bedelivered to the host upon engagement of the bolus constraint. Forexample, suppose the host is relatively insulin resistant and has acorrection factor of 10:1 (e.g., 1 U of insulin will lower glucose by 10mg/dl). Accordingly, 10 U of insulin would be required to lower theglucose level by 100 mg/dl. Suppose the host becomes more insulinsensitive, such as by increasing exercise, which would change hisinsulin needs. The controller module monitors these metabolic changesand adjusts calculation of the insulin therapy accordingly, such bymodifying the correction factor (e.g., increase to 20:1) during insulintherapy calculation, for example. In preferred embodiments, intelligentand dynamic tracking of trends and calculation of bolus insulintherapies enables the dynamic bolus controller module to substantiallyminimize the risk of driving the host into a potentially dangerousstate, such as but not limited to a severely hypoglycemic state (e.g.,glucose concentration less than about 60 mg/dl).

In one exemplary embodiment, the controller module continually receivesinformation (e.g., internally derived data) related to the host'sglucose level and iteratively evaluates the data relative to a targetglycemic range (e.g., a euglycemic range pre-set by the host, acaretaker of the host, or by the manufacturer, such as 80-120 mg/dl or100-140 mg/dl). When the host selects a bolus constraint (e.g., 15 U tobe delivered over the next hour, selected at the start of a meal), thecontroller module evaluates the internally derived data relative to theengaged constraint and calculates an insulin therapy that both 1) issufficient to lower the host's glucose level to and/or within the targetrange and 2) is within the therapy associated with the engaged bolusconstraint (e.g., will not exceed 15 U to be delivered over the nexthour). If the calculated dose is less than or equal to the doseassociated with the engaged constraint, the system delivers thecalculated dose (e.g., a portion of the bolus dose). Generally, it willtake some time for the insulin to have its effect (e.g., related to theinsulin's TAP). In this embodiment, the controller module is configuredto wait the appropriate period of time and then evaluate the host'sresponse to the delivered insulin dose. In some circumstances, thehost's response to the delivered insulin therapy may be insufficient(e.g., his glucose was not lowered to and/or maintained within thetarget range), so, the controller module will calculate and deliver anadditional insulin dose (e.g., another portion of the dynamic bolusdose), based upon evaluation of the internally derived data. Thisiterative process continues until the time defined by the engaged bolusconstraint expires (e.g., the 1-hour has passed). In some circumstances,the host's response to the initial insulin dose may be sufficient tomaintain the host's blood glucose within the target range and additionalinsulin doses will not be calculated/delivered. While not wishing to bebound by theory, it is believed that the dynamic bolus controller moduleenables the use of less insulin while at the same time reducing thenumber of host hypoglycemic events than is possible using model-basedsystems or manual bolus calculation.

In one exemplary embodiment, the controller module of the system 10 isconfigured to continuously (e.g., continually, iteratively,intermittently, automatically, periodically) collect and/or evaluateinternally derived data, including trend data, such as but not limitedto the host's insulin sensitivity and metabolic profile. The controllermodule can be an on/off, dynamic basal and/or dynamic bolus controllermodule, and is configured to adaptively adjust to a newly determinedmetabolic profile when calculating an insulin therapy. In someembodiments, the system is configured to adjust the target range, theset point, the basal profile and/or the bolus constraint, so as toimprove the accuracy of host glucose control. In some embodiments, thesystem (e.g., the electronics module) includes one controller module. Inother embodiments, the system includes two controller modules, which areconfigured to work in concert with each other. For example, the systemcan include an on/off controller module and either the dynamic basal ordynamic bolus controller modules. In another example, the system caninclude the dynamic basal and dynamic bolus controller modules. In yetanother embodiment, the system includes all three controller modules,which are configured to work in concert with each other.

In some embodiments, the system is configured such that the user canenter an insulin dose to be delivered. In some further embodiments, thesystem can be configured such that the controller module evaluates theinternally derived data and calculates an appropriate and/or optimaldelivery schedule for the entered dose. In some further embodiments, thesystem can be configured to deliver the entered dose substantiallyimmediately.

Intelligent and Adaptive Data Evaluation and Therapy Calculation

A host's insulin requirements can fluctuate over time, due to changes ina variety of factors, such as but not limited to changes in the host'shealth, weight and/or exercise routine, changes in the type of insulinused and medications, dietary changes, and the like. Additionally, thecondition of some components of the integrated system 10 can vary,either over time or from lot to lot. For example, many glucose sensorshave some error in their function. This error can vary through out thesensor's lifetime and/or from manufacturing lot to manufacturing lot.Similarly, insulin formulations can vary between manufacturing lots,such as due to small variations in dilution or activity. In yet anotherexample, the insulin deliver device can have some amount of error inmeasurement of insulin being delivered and/or remaining. Accordingly, insome embodiments, the system is configured to intelligently andadaptively adjust to changing circumstances (e.g., account for error indifferent system components when determining an insulin therapy), suchthat the host can be continuously provided with substantially optimumglucose control.

In some circumstances, one or more of the system 10 components have someamount of error. For example, in some circumstances, glucose data from acontinuous glucose sensor may include some sensor error, such as about1%, 2%, 5%, 10%, 15%, 20% or more error. In another example, in somecircumstances, an insulin infusion device can have some error inmeasurement of the amount of insulin delivered (e.g., number of units,rate, volume, and the like) such as about 1%, 2%, 5%, 10%, 15%, 20% ormore error. In yet another example, there can be small errors made whenthe insulin is formulated, such that it can have a slightly differentactivity or concentration than as labeled. Such system error can make itmore difficult to control and host's glucose concentration, unless thesystem is configured to handle this error.

Accordingly, in some embodiments, the system 10 is configured such thatthe controller module (e.g., on/off, dynamic basal or dynamic boluscontroller module) considers system error (e.g., sensor error, insulinactivity/delivery errors) when calculating an insulin therapy (e.g., aninsulin delivery rate, an insulin dose, selecting between the on and offinstructions). In one exemplary embodiment, if an average sensor erroris initially ±20%, then the controller module is configured to adjustthe target glucose range by a similar amount up or down. Accordingly, ifthe original target range is 100-150 mg/dl, then the target range can beincreased by 20% to about 120-180-gm/dl. This can prevent inadvertentlydriving the host too low (e.g., wherein the host's blood sugar is tooclose to a dangerous hypoglycemic level), such as by overshooting thetarget range (e.g., 100- to 150 mg/dl reduced by 20% would be 80- to 130mg/dl). In another exemplary embodiment, the controller module isconfigured to track and/or evaluate system error (e.g., over time) andadjust one or more system parameters (e.g., target range, glucoseboundary, bolus constraint, basal profile, rate if insulin delivery,time of insulin delivery and the like) such that the host is maintainedsubstantially within the target range a substantial portion of the timethe system 10 is in use (e.g., 50, 60, 70, 80, 90, or 99% of the time).For example, if sensor error increases to 30% on day-3 of use, thecontroller module is configured to adjust the target range acorresponding amount (e.g., increase the target range by 30%).

In some embodiments, the system 10 is includes two or all threecontroller modules which are configured to work in concert (e.g., switchtherebetween), such that the host is maintained substantially within thetarget range a substantial portion of the time (e.g., 50%, 60%, 70%,80%, 90%, 95% or more of the time) that the system is in use by thehost. For example, in some embodiments, the system includes an on/offcontroller module and either a dynamic bolus controller module or adynamic basal controller module. In some embodiments, the systemincludes both the dynamic basal and dynamic bolus controller modules,but not an on/off controller module. In some embodiments, the systemincludes the on/off controller module as well as both the dynamic basaland dynamic bolus controller modules.

In one exemplary embodiment, the system includes on/off and basalcontroller modules, and is configured such that determination of insulintherapy occurs in at least two steps. In a first step, the on/offcontroller module evaluates the internally derived data relative to aglucose boundary, and selects between the on and off instructions. Ifthe on instruction is selected, the dynamic basal controller moduleevaluated the internally derived data relative to a programmed basalprofile and calculated/determines an insulin therapy within the currenttime block of the basal profile. If the off instruction is selected,then insulin delivery is terminated. In a further exemplary embodiment,the system also includes a dynamic bolus controller module. In general,the on/off and basal controller modules can be configured to functionautomatically (e.g., perform their functions automatically and inconcert with each other) until the user engages a programmable bolusconstraint. When the user engages the bolus constraint, the boluscontroller module calculates an insulin therapy within the engagedconstraint. The system can be further configured to return to operationby the on/off and basal controller modules, until such time that theuser again engages a bolus constraint. While not wishing to be bound bytheory, it is believed that an intelligent, adaptive integrated system,which can switch between controller modules, can substantially improveconsistency and accuracy of glucose control, which enables tight controlby the host, and thereby improving the host's health and delayingdiabetic complications.

In an exemplary embodiment of a fully automated integrated system 10,the system includes on/off, dynamic basal and dynamic bolus controllermodules, is configured for use in conjunction with a flash insulin, andis configured to adaptively and intelligently switch (e.g.,automatically, as described herein) between controller modules,depending upon evaluation of the internally derived data, systemparameters (e.g., glucose boundary, target range, basal profile, bolusconstraints, and the like) and system constraints, such that the host ismaintained substantially at within a programmed target range at least50% of the time the system is in use. In preferred embodiments, the hostis maintained within the target range at least 60, 70, 80, 90, or 99% ofthe time the system is in use. More preferably, the system is furtherconfigured to maintain the host within the programmed target rangeregardless of the host's activity level, metabolic state and/or mealconsumption. In such a system, a substantial portion of the host's day,he may experience only moderate increases/decreases in glucose. Duringthese portions of his day, the on/off controller can select either theon or off instructions (e.g., to turn insulin delivery on and off), andwhen the on instruction is selected, the basal controller module cancalculate delivery of basal levels of insulin. A portion of the host'sday, an unexpected rapid rise in glucose concentration (e.g., theinternally derived data) may occur, which may indicate that a meal isbeing or has been consumed. Generally, the host would require a bolusinsulin therapy to handle the increased glucose that can result frommeal consumption. Accordingly, the system can be configured such thatthe on/off controller can select the on instruction (e.g., turns oninsulin delivery) and then the dynamic bolus controller module cancalculate an appropriate bolus insulin therapy (e.g., withinpre-programmed bolus constraints, non-host engageable). Similarly, asthe glucose concentration is brought into the target range, the systemcan intelligently recognize a decreased requirement for insulin, and canswitch from the dynamic bolus controller module, back to the dynamicbasal controller module, which can calculate a basal insulin therapy(e.g., for the host's current needs). If the glucose is brought withinthe target range, the on/off controller can select the off instructionto terminate insulin delivery.

Examples

In one exemplary implementation of the preferred embodiments, thecontinuous glucose sensor (and its receiver) comprises programming totrack a host during hypoglycemic or near-hypoglycemic conditions. Inthis implementation, the processor (e.g., controller module) includesprogramming that sends instructions to administer a hypoglycemictreating medicament, such as glucagon, via an implantable pump or thelike, when the glucose level and rate of change surpass a predeterminedthreshold (for example, 80 mg/dL and 2 mg/dL/min). In this situation,the sensor waits a predetermined amount of time (for example, 40minutes), while monitoring the glucose level, rate of change of glucose,and/or acceleration/deceleration of glucose in the host, wherein if therate of change and/or acceleration shows a changing trend away fromhypoglycemia (for example, decreased deceleration of glucose levels tonon-hypoglycemia, then the host need not be alarmed. In this way, theautomated glucagon delivery device can proactively preempt hypoglycemicconditions without alerting or awaking the host.

In one exemplary implementation of the preferred embodiments, acontinuous glucose sensor is integrated with a continuous medicamentdelivery device (for example, an insulin pump) and a bolus medicamentdelivery device (for example, and insulin pen) and a controller module.In this embodiment, the integration exploits the benefits of automatedand semi-automated device, for example, providing an automatedintegration with an infusion pump, while provide semi-automatedintegration with an insulin pen as necessary.

In one exemplary implementation of the preferred embodiments, amedicament delivery device is provided that includes reservoirs of bothfast acting insulin and slow acting insulin. The medicament deliverydevice is integrated with a controller module as described elsewhereherein, however in this implementation, the controller module determinesan amount of fast acting insulin and an amount of slow acting insulin,wherein the medicament delivery device is configured to deliver the twoinsulins separately and/or in combination, such that the host ismaintained substantially at and/or within the target range. In this way,the receiver and medicament delivery device can work together in afeedback loop to iteratively optimize amounts of slow and fast actinginsulin for a variety of situations (for example, based on glucoselevel, rate of change, acceleration, and behavioral factors such asdiet, exercise, time of day, etc.) adapted to the individual host'smetabolic profile.

In one exemplary implementation of the preferred embodiments, anintegrated hypo- and hyper-glycemic treating system is provided. In thisimplementation, a manual-, semi-automated, or automated integration ofan insulin delivery device is combined with a manual-, semi-automated,or automated integration of a glucose or glucagon delivery device. Thesedevices are integrated with the receiver for the continuous glucosesensor and a controller module in any manner described elsewhere herein.While not wishing to be bound by theory, it is believed that thecombination of a continuous glucose sensor, integrated insulin device,and integrated glucose or glucagon device provides a simplified,comprehensive, user friendly, convenient, long-term and continuousmethod of monitoring, treating, and optimizing comprehensive care fordiabetes.

In one exemplary implementation of the preferred embodiments, anintegrated hypo- and hyper-glycemic treating system is provided,including a continuous glucose sensor, an insulin infusion device and adynamic controller module, wherein the system is configured toadaptively and intelligently evaluate the host's metabolic state (e.g.,historical profile) and adjust the insulin therapy accordingly, inresponse to an unexpected increase in glucose above a programmed targetrange. In some circumstances, the boundaries between low, target andhigh glucose levels, between slow and fast rates of change, and betweensmall and large insulin dose adjustments can be substantially sharp.Accordingly, in this embodiment, the dynamic controller module isconfigured to evaluate weighted sums (e.g., derived by processing thedata collected from the continuous glucose sensor, use of a Kalmanfilter) to provide a suggested dynamic insulin therapy that issubstantially adjusted for the host's current glucose profile (e.g.,concentration, rate of change, acceleration, etc.). One skilled in theart understands that, generally, the weighting of a control actiondepends upon the degree to which its input condition is true. Thus, atthe present time (T₁), the condition that best describes the glucoselevel and rate of change (e.g., at T₁) will have the largest influenceon the control action (e.g., the amount of insulin to be calculated).For exemplary purposes, suppose the following conditions are defined: avery high glucose concentration is greater than 140 mg/dl; a moderatelyhigh glucose concentration is from 110 mg/dl to 140 mg/dl; a slow risein glucose concentration is from 0.5 mg/dl/min to 1.0 mg/dl/min; and astable glucose concentration is from −0.5-mg/di/min to 0.5 mg/di/min.Thus, if the measured glucose concentration is 140 mg/dl and it isrising at a rate of 0.5=mg/dl/min, then the host's current glucoseprofile falls on the boundary between very high and a little highglucose concentrations, as well as between rising slowly and stablerates. Accordingly, if a large insulin dose increase is defined as from1-U/h to 2-U/h; a moderate dose increase as from 0.5-U/h to 1-U/h; andsmall dose increase as from 0.1-U/h to 0.5-U/h; then an optimal increasein insulin dose (e.g., to maintain the host in the target range) may beabout 1.2-U/h, for example. Similarly, if the host is relatively insulininsensitive (e.g., resistant), a larger dose can be calculated; and ifthe host is relatively insulin sensitive, then a smaller dose can becalculated. Thus, the dynamic controller module is configured to adapt(e.g., adjust, modify, re-program) insulin therapy (e.g., dosing) to agiven host and his current metabolic conditions. For example, thedynamic controller module can be configured to monitor (e.g., learn) thehost's insulin sensitivity by comparing substantially more recent (priorminutes to hours) changes in glucose and insulin dose, and adjust thecurrent dose boundaries accordingly. In a further example, the systemcan consider system error (e.g., sensor error, drug delivery error andthe like) as a weighted sum, when determining the dynamic insulintherapy. For example, if the sensor error is very high and the rate ofchange is rising slowly, then the insulin therapy can be adjusted by alarge increase; if the sensor error is very high and the rate of changeis stable, then the insulin therapy can be adjusted by a mediumincrease; if the sensor error is a little high and the rate of change isstable, then the insulin therapy can be adjusted by a small increase.Advantageously, because any definition of boundaries between low, targetand high glucose levels, between slow and fast rates of change, andbetween small and large insulin therapy adjustments is artificiallysharp, the weighted sum provides a graded dose adjustment. Because thedynamic controller module is configured adaptively learn and tracktrends, the dose boundaries can be intelligently adjusted accordingly.While not wishing to be bound by theory, it is believed that due to itsnon-model-based nature, smooth transitions between ranges and adaptivelearning, the dynamic controller module substantially increases accuracyfor each host, which leads to a higher level of safety and improved hosthealth.

In one exemplary implementation of the preferred embodiments, anintegrated hypo- and hyper-glycemic treating system is provided,including a continuous glucose sensor, an insulin infusion device and acontroller module (on/off, dynamic basal, dynamic bolus) configured tomonitor and evaluate system error (e.g., errors in sensor readingsand/or evaluation of the internally derived data) and to titrate theinsulin therapy, such that the host substantially does not overshoot theeuglycemic range (e.g., enter the hypoglycemic range) during delivery ofthe calculated dose. For example, if the sensor readings include a ±30%error, the target range is set an equivalent percent (e.g., ±30%) abovethe target range. For example, in some circumstances, if the preferredtarget range is 80-100 mg/dl, the target can be increased by 30%, to110-140 mg/dl glucose. In other circumstances, the internally deriveddata can indicate that the target range should be lowered. Accordingly,the target range can be adjusted up or down, depending upon the error ofthe system, such that the host substantially does not enter ahypoglycemic (e.g., unsafe) glucose range.

In one exemplary implementation of the preferred embodiments, anintegrated hypo- and hyper-glycemic treating system is provided,including a continuous glucose sensor, an insulin infusion device and acontroller module configured to provide and/or evaluate trendinginformation. Trend information can include changes in glucoseconcentration (increasing or decreasing), the rate of change, and theacceleration. Generally, consideration of trend information in insulintherapy calculation can direct relative increases and/or decreases inthe calculated therapy and its delivery. For example, in a firstexemplary circumstance, the host's glucose concentration is 200 mg/dland slowly increasing; 5 U of insulin might be insufficient to bring hisglucose down to the target level (e.g., 100 mg/dl). In a secondexemplary circumstance, in contrast, if the host's glucose concentrationis 200 mg/dl and rapidly decreasing, that same insulin dose (e.g., 5 U)might be too large and cause him to overshoot the target range (e.g.,become hypoglycemic). In still another example, if the host's glucoseconcentration is 200 mg/dl and increasing rapidly, a larger insulin dose(e.g., 6, 7, 8, 9 or 10 U or more) may be required to bring his glucosesubstantially to the target range, relative to the dose required in thefirst exemplary circumstance. Accordingly, the controller module isconfigured to evaluate the trend information when calculating amedicament therapy.

In one exemplary implementation of the preferred embodiments, anintegrated hypo- and hyper-glycemic treating system is provided,including a continuous glucose sensor, an insulin infusion device and acontroller module, wherein the target range is a euglycemic glucoserange (e.g., about 90 mg/dl to 140 mg/dl), a dynamic insulin therapy isan amount of a given insulin required to lower a hyperglycemic host'sglucose concentration substantially to within about 90 mg/dl to 140mg/dl glucose (e.g., at the time of calculation), substantially withoutreducing the host's glucose to a hypoglycemic range. Suppose the targetrange is 100-140 mg/dl, the host's current glucose concentration is 120mg/dl and he has just consumed a meal (e.g., including an amount ofcarbohydrate). Generally, in response to the meal, the host's glucosewill begin to rise. Preferably, the integrated system monitor's thehost's glucose substantially continuously. If the host's glucose exceeds140 mg/dl (e.g., at T₁), then the dynamic controller module willcalculate a dynamic insulin dose (e.g., D₁) sufficient (at time T₁) tolower the host's glucose to at least 140 mg/dl. After delivery of D₁,the system will continue to monitor the host's glucose. Generally, aperiod of time sufficient for the insulin to act (e.g., depending uponthe insulin's TAP) is allowed to pass. If, at a later time (e.g., T₂),the host's glucose exceeds 140 mg/dl, the dynamic controller module cancalculate another dynamic insulin dose (e.g., D₂), sufficient (at timeT₂) to lower the host's glucose to at least 140 mg/dl. If, at T₂, thehost's glucose is within the target range, then no additional dynamicinsulin doses will be calculated and/or delivered. This process can berepeated (e.g., iteratively), such that the host's glucose is maintainedsubstantially within the target range (e.g., 100-140 mg/dl in thisexample). In preferred embodiments, the system is configured to stopinsulin delivery and/or sound an alarm, if the host's glucose fallsbelow the target range and/or within a dangerous range (e.g.,hypoglycemic, such as less than 70 mg/dl).

In one exemplary implementation of the preferred embodiments, anintegrated hypo- and hyper-glycemic treating system is provided,including a continuous glucose sensor, an insulin infusion device and acontroller module, the dynamic controller module is configured tocalculate an insulin therapy that, in a worst-case scenario, is notsufficient (e.g., insufficient) to drive the host into a severelyhypoglycemic state (e.g., less than about 65 mg/dl). For exemplarypurposes, let's suppose that the host's target glucose is 110 mg/dl, andhis glucose level is currently increasing at >1 mg/dl/min and isprojected to rise (based on the internally derived data) to 170 mg/dl.The dynamic controller module can be programmed such that at aprogrammed threshold level (e.g., 140 mg/dl), it calculates an insulintherapy that will be sufficient to lower the host's glucoseconcentration from the expected 170 mg/dl down to the target range (110mg/dl; lowered by ˜60 mg/dl). Suppose that the host's glucose actuallydoes not rise above 140 mg/dl. In this circumstance, the 60-pointcorrection will lower glucose to about 80 mg/dl, which is still about20-30 mg/dl above what would be a dangerously hypoglycemic glucoseconcentration. On the other hand, in a best-case scenario, the dynamiccontroller module can anticipate and correct/prevent an expected rise inglucose concentration, such that the host is substantially maintainedwithin a target blood glucose range, such as a euglycemic range. If thehost's glucose concentration continues to rise after delivery of theinsulin therapy (e.g., to 200 mg/dl), the dynamic controller module cancalculate an additional insulin therapy sufficient to lower the host'sglucose concentration the additional amount (e.g., 30-points). In someembodiments, the dynamic controller module is configured to divide theinsulin therapy into two or more portions to be delivered over a givenperiod of time. For example, if the insulin therapy is divided into twoportions, the first portion can be delivered, and the host's responsemonitored. If, after the monitoring period has passed, the host'sglucose concentration is still above the target, the second portion (allor a part thereof) can be delivered. If, on the other hand, the host'sglucose concentration has been lowered to within a threshold (e.g.,110-140 mg/dl) or to the target range (e.g., 110 mg/dl), the secondportion can be not delivered.

Methods and devices that are suitable for use in conjunction withaspects of the preferred embodiments are disclosed in U.S. Pat. No.4,994,167; U.S. Pat. No. 4,757,022; U.S. Pat. No. 6,001,067; U.S. Pat.No. 6,741,877; U.S. Pat. No. 6,702,857; U.S. Pat. No. 6,558,321; U.S.Pat. No. 6,931,327; U.S. Pat. No. 6,862,465; U.S. Pat. No. 7,074,307;U.S. Pat. No. 7,081,195; U.S. Pat. No. 7,108,778; and U.S. Pat. No.7,110,803.

Methods and devices that are suitable for use in conjunction withaspects of the preferred embodiments are disclosed in U.S. PatentPublication No. US-2005-0176136-A1; U.S. Patent Publication No.US-2005-0251083-A1; U.S. Patent Publication No. US-2005-0143635-A1; U.S.Patent Publication No. US-2005-0181012-A1; U.S. Patent Publication No.US-2005-0177036-A1; U.S. Patent Publication No. US-2005-0124873-A1; U.S.Patent Publication No. US-2005-0115832-A1; U.S. Patent Publication No.US-2005-0245799-A1; U.S. Patent Publication No. US-2005-0245795-A1; U.S.Patent Publication No. US-2005-0242479-A1; U.S. Patent Publication No.US-2005-0182451-A1; U.S. Patent Publication No. US-2005-0056552-A1; U.S.Patent Publication No. US-2005-0192557-A1; U.S. Patent Publication No.US-2005-0154271-A1; U.S. Patent Publication No. US-2004-0199059-A1; U.S.Patent Publication No. US-2005-0054909-A1; U.S. Patent Publication No.US-2005-0112169-A1; U.S. Patent Publication No. US-2005-0051427-A1; U.S.Patent Publication No. US-2003-0032874-A1; U.S. Patent Publication No.US-2005-0103625-A1; U.S. Patent Publication No. US-2005-0203360-A1; U.S.Patent Publication No. US-2005-0090607-A1; U.S. Patent Publication No.US-2005-0187720-A1; U.S. Patent Publication No. US-2005-0161346-A1; U.S.Patent Publication No. US-2006-0015020-A1; U.S. Patent Publication No.US-2005-0043598-A1; U.S. Patent Publication No. US-2003-0217966-A1; U.S.Patent Publication No. US-2005-0033132-A1; U.S. Patent Publication No.US-2005-0031689-A1; U.S. Patent Publication No. US-2004-0186362-A1; U.S.Patent Publication No. US-2005-0027463-A1; U.S. Patent Publication No.US-2005-0027181-A1; U.S. Patent Publication No. US-2005-0027180-A1; U.S.Patent Publication No. US-2006-0020187-A1; U.S. Patent Publication No.US-2006-0036142-A1; U.S. Patent Publication No. US-2006-0020192-A1; U.S.Patent Publication No. US-2006-0036143-A1; U.S. Patent Publication No.US-2006-0036140-A1; U.S. Patent Publication No. US-2006-0019327-A1; U.S.Patent Publication No. US-2006-0020186-A1; U.S. Patent Publication No.US-2006-0020189-A1; U.S. Patent Publication No. US-2006-0036139-A1; U.S.Patent Publication No. US-2006-0020191-A1; U.S. Patent Publication No.US-2006-0020188-A1; U.S. Patent Publication No. US-2006-0036141-A1; U.S.Patent Publication No. US-2006-0020190-A1; U.S. Patent Publication No.US-2006-0036145-A1; U.S. Patent Publication No. US-2006-0036144-A1; U.S.Patent Publication No. US-2006-0016700-A1; U.S. Patent Publication No.US-2006-0142651-A1; U.S. Patent Publication No. US-2006-0086624-A1; U.S.Patent Publication No. US-2006-0068208-A1; U.S. Patent Publication No.US-2006-0040402-A1; U.S. Patent Publication No. US-2006-0036142-A1; U.S.Patent Publication No. US-2006-0036141-A1; U.S. Patent Publication No.US-2006-0036143-A1; U.S. Patent Publication No. US-2006-0036140-A1; U.S.Patent Publication No. US-2006-0036139-A1; U.S. Patent Publication No.US-2006-0142651-A1; U.S. Patent Publication No. US-2006-0036145-A1; U.S.Patent Publication No. US-2006-0036144-A1; U.S. Patent Publication No.US-2006-0200022-A1; U.S. Patent Publication No. US-2006-0198864-A1; U.S.Patent Publication No. US-2006-0200019-A1; U.S. Patent Publication No.US-2006-0189856-A1; U.S. Patent Publication No. US-2006-0200020-A1; U.S.Patent Publication No. US-2006-0200970-A1; U.S. Patent Publication No.US-2006-0183984-A1; U.S. Patent Publication No. US-2006-0183985-A1; U.S.Patent Publication No. US-2006-0195029-A1; U.S. Patent Publication No.US-2006-0229512-A1; U.S. Patent Publication No. US-2006-0222566-A1; U.S.Patent Publication No. US-2007-0032706-A1; U.S. Patent Publication No.US-2007-0016381-A1; U.S. Patent Publication No. US-2007-0027370-A1; U.S.Patent Publication No. US-2007-0027384-A1; U.S. Patent Publication No.US-2007-0032717-A1; and U.S. Patent Publication No. US-2007-0032718 A1.

Methods and devices that are suitable for use in conjunction withaspects of the preferred embodiments are disclosed in U.S. applicationSer. No. 09/447,227 filed Nov. 22, 1999 and entitled “DEVICE AND METHODFOR DETERMINING ANALYTE LEVELS”; U.S. application Ser. No. 11/515,342filed Sep. 1, 2006 and entitled “SYSTEMS AND METHODS FOR PROCESSINGANALYTE SENSOR DATA”; U.S. application Ser. No. 11/654,135 filed Jan.17, 2007 and entitled “POROUS MEMBRANES FOR USE WITH IMPLANTABLEDEVICES”; U.S. application Ser. No. 11/675,063 filed Feb. 14, 2007 andentitled “ANALYTE SENSOR”; U.S. application Ser. No. 11/543,734 filedOct. 4, 2006 and entitled “DUAL ELECTRODE SYSTEM FOR A CONTINUOUSANALYTE SENSOR”; U.S. application Ser. No. 11/654,140 filed Jan. 17,2007 and entitled “MEMBRANES FOR AN ANALYTE SENSOR”; U.S. applicationSer. No. 11/654,327 filed Jan. 17, 2007 and entitled “MEMBRANES FOR ANANALYTE SENSOR”; U.S. application Ser. No. 11/543,396 filed Oct. 4, 2006and entitled “ANALYTE SENSOR”; U.S. application Ser. No. 11/543,490filed Oct. 4, 2006 and entitled “ANALYTE SENSOR”; U.S. application Ser.No. 11/543,404 filed Oct. 4, 2006 and entitled “ANALYTE SENSOR”; U.S.application Ser. No. 11/681,145 filed Mar. 1, 2007 and entitled “ANALYTESENSOR”; and U.S. application Ser. No. 11/690,752 filed Mar. 23, 2007and entitled “TRANSCUTANEOUS ANALYTE SENSOR”.

All references cited herein, including but not limited to published andunpublished applications, patents, and literature references, areincorporated herein by reference in their entirety and are hereby made apart of this specification. To the extent publications and patents orpatent applications incorporated by reference contradict the disclosurecontained in the specification, the specification is intended tosupersede and/or take precedence over any such contradictory material.

The term “comprising” as used herein is synonymous with “including,”“containing,” or “characterized by,” and is inclusive or open-ended anddoes not exclude additional, unrecited elements or method steps.

All numbers expressing quantities of ingredients, reaction conditions,and so forth used in the specification are to be understood as beingmodified in all instances by the term “about.” Accordingly, unlessindicated to the contrary, the numerical parameters set forth herein areapproximations that may vary depending upon the desired propertiessought to be obtained. At the very least, and not as an attempt to limitthe application of the doctrine of equivalents to the scope of anyclaims in any application claiming priority to the present application,each numerical parameter should be construed in light of the number ofsignificant digits and ordinary rounding approaches.

The above description discloses several methods and materials of thepresent invention. This invention is susceptible to modifications in themethods and materials, as well as alterations in the fabrication methodsand equipment. Such modifications will become apparent to those skilledin the art from a consideration of this disclosure or practice of theinvention disclosed herein. Consequently, it is not intended that thisinvention be limited to the specific embodiments disclosed herein, butthat it cover all modifications and alternatives coming within the truescope and spirit of the invention.

What is claimed is:
 1. An integrated system for monitoring a glucoseconcentration in a host and for delivering insulin to the host, thesystem comprising: a continuous glucose sensor, wherein the continuousglucose sensor is configured to substantially continuously measure aglucose concentration in a host, and to provide sensor data associatedwith the glucose concentration of the host; an electronics modulecomprising a basal controller module configured to iteratively determinean insulin therapy instruction in response to an evaluation of arelationship of internally derived data and a basal profile, wherein thebasal profile comprises at least one time block associated with amaximum insulin delivery rate; and an insulin delivery device configuredto deliver insulin to the host, wherein the insulin delivery device isat least one of physically connected to a receiver and/or operablyconnected to a receiver, wherein the insulin delivery device isconfigured to receive the insulin therapy instruction from the basalcontroller module, and wherein the insulin therapy instruction isconstrained by a maximum insulin delivery rate associated with a currenttime block.
 2. The integrated system of claim 1, wherein the insulintherapy instruction is determined solely on internally derived data andthe basal profile.
 3. The integrated system of claim 1, wherein themaximum insulin delivery rate is an insulin delivery rate of from about0.01 U/hour to about 6.0 U/hour.
 4. The integrated system of claim 1,wherein the insulin delivery device is configured to deliver insulinautomatically in response to receiving the insulin therapy instruction.5. The integrated system of claim 1, wherein the insulin therapyinstruction instructs delivery of insulin at less than the maximuminsulin delivery rate associated with the current time block.
 6. Theintegrated system of claim 1, wherein the basal controller module isconfigured to iteratively determine the insulin therapy instruction inresponse to internally derived data and the basal profile, wherein thebasal controller module comprises programming to adjust the basalprofile in response to internally derived data.
 7. The integrated systemof claim 6, wherein the basal controller module is further configured toiteratively determine the insulin therapy instruction in response to ahost's metabolic response to an insulin therapy, wherein the basalcontroller module comprises programming to adjust the basal profile inresponse to the host's metabolic response.
 8. The integrated system ofclaim 1, wherein the insulin delivery device is configured to providedelivery device data associated with insulin delivery.
 9. The integratedsystem of claim 8, wherein the internally derived data comprises atleast one of sensor data, processed sensor data, delivery device data,or processed delivery device data.
 10. The integrated system of claim 9,wherein the internally derived data further comprises at least one of aglucose concentration, a glucose concentration range, a change inglucose concentration, a glucose concentration rate of change, anacceleration of a glucose concentration rate of change, a host insulinsensitivity, a change in host insulin sensitivity, a host metabolicresponse to insulin therapy, an amount of insulin delivered, a time ofinsulin delivery, an insulin on board, or a time.
 11. The integratedsystem of claim 9, further comprising an auxiliary sensor configured toprovide auxiliary sensor data associated with at least one measurementmade by the auxiliary sensor in the host, wherein the internally deriveddata further comprises auxiliary sensor data.
 12. The integrated systemof claim 11, wherein the auxiliary sensor comprises at least one of anaccelerometer, a pressure sensor, a pH sensor, a temperature sensor, anoxygen sensor, an auxiliary glucose sensor, an analyte sensor configuredto measure an analyte other than glucose, a proximity sensor, or anorientation sensor.
 13. An method for monitoring a glucose concentrationin a host and for delivering insulin to the host, the method comprising:receiving sensor data associated with a glucose concentration of a host;evaluating of a relationship of internally derived data and a basalprofile; determining, using a basal controller module of a processor, aninsulin therapy instruction in response to the evaluation, wherein thebasal profile comprises at least one time block associated with amaximum insulin delivery rate; and delivering insulin to the host basedon the insulin therapy instruction from the basal controller module,wherein the insulin therapy instruction is constrained by a maximuminsulin delivery rate associated with a current time block.
 14. Themethod of claim 13, wherein the determining is based solely on theinternally derived data and the basal profile.
 15. The method of claim13, wherein the maximum insulin delivery rate is an insulin deliveryrate of from about 0.01 U/hour to about 6.0 U/hour.
 16. The method ofclaim 13, wherein the delivering insulin is automatic in response todetermining the insulin therapy instruction.
 17. The method of claim 13,w wherein the insulin therapy instruction instructs delivery of insulinat less than the maximum insulin delivery rate associated with thecurrent time block.
 18. The method of claim 13, wherein the determiningcomprises iteratively determining the insulin therapy instruction andadjusting the basal profile in response to internally derived data. 19.The method of claim 18, wherein the determining comprises iterativelydetermining the insulin therapy instruction and adjusting the basalprofile in response to a host's metabolic response to an insulintherapy.
 20. The method of claim 13, comprising providing deliverydevice data associated with insulin delivery.
 21. The method of claim20, wherein the internally derived data comprises at least one of sensordata, processed sensor data, delivery device data, or processed deliverydevice data.
 22. The method of claim 21, wherein the internally deriveddata comprises at least one of a glucose concentration, a glucoseconcentration range, a change in glucose concentration, a glucoseconcentration rate of change, an acceleration of a glucose concentrationrate of change, a host insulin sensitivity, a change in host insulinsensitivity, a host metabolic response to insulin therapy, an amount ofinsulin delivered, a time of insulin delivery, an insulin on board, or atime.
 23. The method of claim 21, further comprising providing auxiliarysensor data associated with at least one measurement made by anauxiliary sensor associated with the host, wherein the internallyderived data comprises the auxiliary sensor data.
 24. The method ofclaim 23, wherein the auxiliary sensor data comprises at least one of anaccelerometer, a pressure sensor, a pH sensor, a temperature sensor, anoxygen sensor, an auxiliary glucose sensor, an analyte sensor configuredto measure an analyte other than glucose, a proximity sensor, or anorientation sensor.